Targeted Sequencing Reveals Large-Scale Sequence Polymorphism in Maize Candidate Genes for Biomass Production and Composition

Sequence variations associated with novel purple-pericarp super-sweetcorn compared to its purple-pericarp maize and white super-sweetcorn parents

Recently, a novel purple-pericarp super-sweetcorn line, 'Tim1' (A1A1.sh2sh2) was derived from the purple-pericarp maize 'Costa Rica' (A1Sh2.A1Sh2) and white shrunken2 (sh2) super-sweetcorn 'Tims-white' (a1sh2.a1sh2), however, information regarding anthocyanin biosynthesis genes controlling purple colour and sweetness gene is lacking. Specific sequence differences in the CDS (coding DNA sequence) and promoter regions of the anthocyanin biosynthesis structural genes, anthocyanin1 (A1), purple aleurone1 (Pr1) and regulatory genes, purple plant1 (Pl1), plant colour1 (B1), coloured1 (R1), and the sweetcorn structural gene, shrunken2 (sh2) were investigated using the publicly available annotated yellow starchy maize, B73 (NAM5.0) as a reference genome. In the CDS region, the A1, Pl1 and R1 gene sequence differences of 'Tim1' and 'Costa Rica' were similar, as they control purple-pericarp pigmentation. However, the B1 gene showed similarity between the 'Tim1' and 'Tims-white' lines, which may indicate that it does not have a role in controlling pericarp colour, unlike the report of a previous study. In the case of the Pr1 gene, in contrast to 'Costa Rica', 6- and 8-bp dinucleotide (TA) repeats were observed in the promoter region of the 'Tims-white' and 'Tim1' lines, respectively, indicating the defective functionality (redder colour in 'Tim1' rather than purple in 'Costa Rica') of the recessive pr1 allele. In sweetcorn, the structural gene (sh2), sequence showed similarity between purple-sweet 'Tim1' and its white-sweet parent 'Tims-white', as both display a shrunken phenotype in their mature kernels. These findings revealed that the developed purple-sweet line is different to the reference yellow-nonsweet line in both the anthocyanin biosynthesis and sweetcorn genes.

A Large-Scale Candidate-Gene Association Mapping for Drought Tolerance and Agronomic Traits in Sugarcane

Dissection of the genetic loci controlling drought tolerance traits with a complex genetic inheritance is important for drought-tolerant sugarcane improvement. In this study, we conducted a large-scale candidate gene association study of 649 candidate genes in a sugarcane diversity panel to identify genetic variants underlying agronomic traits and drought tolerance indices evaluated in plant cane and ratoon cane under water-stressed (WS) and non-stressed (NS) environments. We identified 197 significant marker-trait associations (MTAs) in 141 candidate genes associated with 18 evaluated traits with the Bonferroni correction threshold (α = 0.05). Out of the total, 95 MTAs in 78 candidate genes and 62 MTAs in 58 candidate genes were detected under NS and WS conditions, respectively. Most MTAs were found only in specific water regimes and crop seasons. These MTAs explained 7.93-30.52% of phenotypic variation. Association mapping results revealed that 34, 59, and 104 MTAs involved physiological and molecular adaptation, phytohormone metabolism, and drought-inducible genes. They identified 19 pleiotropic genes associated with more than one trait and many genes related to drought tolerance indices. The genetic and genomic resources identified in this study will enable the combining of yield-related traits and sugar-related traits with agronomic value to optimize the yield of sugarcane cultivars grown under drought-stressed and non-stressed environments.

Crop genetic diversity uncovers metabolites, elements, and gene networks predicted to be associated with high plant biomass yields in maize

Rapid population growth and increasing demand for food, feed, and bioenergy in these times of unprecedented climate change require breeding for increased biomass production on the world's croplands. To accelerate breeding programs, knowledge of the relationship between biomass features and underlying gene networks is needed to guide future breeding efforts. To this end, large-scale multiomics datasets were created with genetically diverse maize lines, all grown in long-term organic and conventional cropping systems. Analysis of the datasets, integrated using regression modeling and network analysis revealed key metabolites, elements, gene transcripts, and gene networks, whose contents during vegetative growth substantially influence the build-up of plant biomass in the reproductive phase. We found that S and P content in the source leaf and P content in the root during the vegetative stage contributed the most to predicting plant performance at the reproductive stage. In agreement with the Gene Ontology enrichment analysis, the cis-motifs and identified transcription factors associated with upregulated genes under phosphate deficiency showed great diversity in the molecular response to phosphate deficiency in selected lines. Furthermore, our data demonstrate that genotype-dependent uptake, assimilation, and allocation of essential nutrient elements (especially C and N) during vegetative growth under phosphate starvation plays an important role in determining plant biomass by controlling root traits related to nutrient uptake. These integrative multiomics results revealed key factors underlying maize productivity and open new opportunities for efficient, rapid, and cost-effective plant breeding to increase biomass yield of the cereal crop maize under adverse environmental factors.

Maize leaves drought-responsive genes revealed by comparative transcriptome of two cultivars during the filling stage

Like other important cereal crop in modern agricultural production, maize is also threatened by drought. And the drought stress during maize filling stage will directly affect the quality (protein or oil concentration) and also the weight of grain. Therefore, different from previous studies focusing on inbred lines and pot experiment at seedling stage, current study selected filling stage of the adult plant and planting maize in the experimental field. Two hybrids cultivars with different drought tolerant were used for drought and water treatment respectively. We performed transcriptome sequencing analysis of 4 groups, 12 samples, and obtained 651.08 million raw reads. Then the data were further processed by mapping to a reference genome, GO annotation, enrichment analysis and so on. Among them we focus on the different change trends of water treatment and drought treatment, and the different responses of two drought-tolerant cultivars to drought treatment. Through the analysis, several transcripts which encode nitrogen metabolic, protein phosphorylation, MYB,AP2/ERF, HB transcriptional factor, O-glycosyl hydrolases and organic acid metabolic process were implicated with maize drought stress. Our data will offer insights of the identification of genes involved in maize drought stress tolerance, which provides a theoretical basis for maize drought resistance breeding.

Optimized DNA extraction and library preparation for minute arthropods: Application to target enrichment in chalcid wasps used for biocontrol

Target enrichment is increasingly used for genotyping of plant and animal species or to better understand the evolutionary history of important lineages through the inference of statistically robust phylogenies. Limitations to routine target enrichment are both the complexity of current protocols and low input DNA quantity. Thus, working with tiny organisms such as microarthropods can be challenging. Here, we propose easy to set up optimizations for DNA extraction and library preparation prior to target enrichment. Prepared libraries were used to capture 1,432 ultraconserved elements (UCEs) from microhymenoptera (Chalcidoidea), which are among the tiniest insects on Earth and the most commercialized worldwide for biological control purposes. Results show no correlation between input DNA quantities (1.8-250 ng, 0.4 ng with an extra whole genome amplification step) and the number of sequenced UCEs on an Illumina MiSeq. Phylogenetic inferences highlight the potential of UCEs to solve relationships within the families of chalcid wasps, which has not been achieved so far. The protocol (library preparation + target enrichment) allows processing 96 specimens in five working days, by a single person, without requiring the use of expensive robotic molecular biology platforms, which could help to generalize the use of target enrichment for minute specimens.

Progress in plant genome sequencing: research directions

Since the first plant genome of Arabidopsis thaliana has been sequenced and published, genome sequencing technologies have undergone significant changes. New algorithms, sequencing technologies and bioinformatic approaches were adopted to obtain genome, transcriptome and exome sequences for model and crop species, which have permitted deep inferences into plant biology. As a result of an improved genome assembly and analysis methods, genome sequencing costs plummeted and the number of high-quality plant genome sequences is constantly growing. Consequently, more than 300 plant genome sequences have been published over the past twenty years. Although many of the published genomes are considered incomplete, they proved to be a valuable tool for identifying genes involved in the formation of economically valuable plant traits, for marker-assisted and genomic selection and for comparative analysis of plant genomes in order to determine the basic patterns of origin of various plant species. Since a high coverage and resolution of a genome sequence is not enough to detect all changes in complex samples, targeted sequencing, which consists in the isolation and sequencing of a specific region of the genome, has begun to develop. Targeted sequencing has a higher detection power (the ability to identify new differences/variants) and resolution (up to one basis). In addition, exome sequencing (the method of sequencing only protein-coding genes regions) is actively developed, which allows for the sequencing of non-expressed alleles and genes that cannot be found with RNA-seq. In this review, an analysis of sequencing technologies development and the construction of “reference” genomes of plants is performed. A comparison of the methods of targeted sequencing based on the use of the reference DNA sequence is accomplished.

SNPSelect: A scalable and flexible targeted sequence-based genotyping solution

In plant breeding the use of molecular markers has resulted in tremendous improvement of the speed with which new crop varieties are introduced into the market. Single Nucleotide Polymorphism (SNP) genotyping is routinely used for association studies, Linkage Disequilibrium (LD) and Quantitative Trait Locus (QTL) mapping studies, marker-assisted backcrosses and validation of large numbers of novel SNPs. Here we present the KeyGene SNPSelect technology, a scalable and flexible multiplexed, targeted sequence-based, genotyping solution. The multiplex composition of SNPSelect assays can be easily changed between experiments by adding or removing loci, demonstrating their content flexibility. To demonstrate this versatility, we first designed a 1,056-plex maize assay and genotyped a total of 374 samples originating from an F2 and a Recombinant Inbred Line (RIL) population and a maize germplasm collection. Next, subsets of the most informative SNP loci were assembled in 384-plex and 768-plex assays for further genotyping. Indeed, selection of the most informative SNPs allows cost-efficient yet highly informative genotyping in a custom-made fashion, with average call rates between 88.1% (1,056-plex assay) and 99.4% (384-plex assay), and average reproducibility rates between duplicate samples ranging from 98.2% (1056-plex assay) to 99.9% (384-plex assay). The SNPSelect workflow can be completed from a DNA sample to a genotype dataset in less than three days. We propose SNPSelect as an attractive and competitive genotyping solution to meet the targeted genotyping needs in fields such as plant breeding.

Identification of induced mutations in hexaploid wheat genome using exome capture assay

Wheat is a staple food crop of many countries. Improving resilience to biotic and abiotic stresses remain key breeding targets. Among these, rust diseases are the most detrimental in terms of depressing wheat production. In the present study, chemical mutagenesis was used to induce mutations in the wheat variety NN-Gandum-1. This cultivar is moderately resistant to leaf and yellow rust. The aim of mutagenesis was to improve resistance to the disease as well as to study function of genes conferring resistance to the disease. In the present investigation, a 0.8% EMS dose was found optimum for supporting 45-55% germination of NN-Gandum-1. A total of 3,634 M2 fertile plants were produced from each of the M1 plant. Out of these, 33 (0.91%) and 20 plants (0.55%) showed absolute resistance to leaf and yellow rust, respectively. While 126 (3.46%) and 127 plants (3.49%) exhibited high susceptibility to the leaf and yellow rust, respectively. In the M4 generation, a total of 11 M4 lines (nine absolute resistant and two highly susceptible) and one wild type were selected for NGS-based exome capture assay. A total of 104,779 SNPs were identified that were randomly distributed throughout the wheat sub genomes (A, B and D). Induced mutations in intronic sequences predominated. The highest total number of SNPs detected in this assay were mapped to chr.2B (14,273 SNPs), which contains the highest number of targeted base pairs in the assay. The average mutation density across all regions interrogated was estimated to be one mutation per 20.91 Mb. The highest mutation frequency was found in chr.2D (1/11.7 kb) and the lowest in chr.7D (1/353.4 kb). Out of the detected mutations, 101 SNPs were filtered using analysis criteria aimed to enrich for mutations that may affect gene function. Out of these, one putative SNP detected in Lr21 were selected for further analysis. The SNP identified in chimeric allele (Lr21) of a resistant mutant (N1-252) was located in a NBS domain of chr.1BS at 3.4 Mb position. Through computational analysis, it was demonstrated that this identified SNP causes a substitution of glutamic acid with alanine, resulting in a predicted altered protein structure. This mutation, therefore, is a candidate for contributing to the resistance phenotype in the mutant line. Based on this work, we conclude that the wheat mutant resource developed is useful as a source of novel genetic variation for forward-genetic screens and also as a useful tool for gaining insights into the important biological circuits of different traits of complex genomes like wheat.

Comparative analysis of the male inflorescence transcriptome profiles of an ms22 mutant of maize

In modern agricultural production, maize is the most successful crop utilizing heterosis. 712C-ms22 is an important male sterile material in maize. In this study, we performed transcriptome sequencing analysis of the V10 stage of male inflorescence. Through this analysis, 27.63 million raw reads were obtained, and trimming of the raw data revealed 26.63 million clean reads, with an average match rate of 94.64%. Using Tophat software, we matched these clean reads to the maize reference genome. The abundance of 39,622 genes was measured, and 35,399 genes remained after filtering out the non-expressed genes across all the samples. These genes were classified into 19 categories by clusters of orthologous groups of protein annotation. Transcriptome sequencing analysis of the male sterile and fertile 712C-ms22 maize revealed some key DEGs that may be related to metabolic pathways. qRT-PCR analysis validated the gene expression patterns identified by RNA-seq. This analysis revealed some of the essential genes responsible for pollen development and for pollen tube elongation. Our findings provide useful markers of male sterility and new insights into the global mechanisms mediating male sterility in maize.

Genomics-Enabled Next-Generation Breeding Approaches for Developing System-Specific Drought Tolerant Hybrids in Maize

Breeding science has immensely contributed to the global food security. Several varieties and hybrids in different food crops including maize have been released through conventional breeding. The ever growing population, decreasing agricultural land, lowering water table, changing climate, and other variables pose tremendous challenge to the researchers to improve the production and productivity of food crops. Drought is one of the major problems to sustain and improve the productivity of food crops including maize in tropical and subtropical production systems. With advent of novel genomics and breeding tools, the way of doing breeding has been tremendously changed in the last two decades. Drought tolerance is a combination of several component traits with a quantitative mode of inheritance. Rapid DNA and RNA sequencing tools and high-throughput SNP genotyping techniques, trait mapping, functional characterization, genomic selection, rapid generation advancement, and other tools are now available to understand the genetics of drought tolerance and to accelerate the breeding cycle. Informatics play complementary role by managing the big-data generated from the large-scale genomics and breeding experiments. Genome editing is the latest technique to alter specific genes to improve the trait expression. Integration of novel genomics, next-generation breeding, and informatics tools will accelerate the stress breeding process and increase the genetic gain under different production systems.

Assessing and Exploiting Functional Diversity in Germplasm Pools to Enhance Abiotic Stress Adaptation and Yield in Cereals and Food Legumes

There is a need to accelerate crop improvement by introducing alleles conferring host plant resistance, abiotic stress adaptation, and high yield potential. Elite cultivars, landraces and wild relatives harbor useful genetic variation that needs to be more easily utilized in plant breeding. We review genome-wide approaches for assessing and identifying alleles associated with desirable agronomic traits in diverse germplasm pools of cereals and legumes. Major quantitative trait loci and single nucleotide polymorphisms (SNPs) associated with desirable agronomic traits have been deployed to enhance crop productivity and resilience. These include alleles associated with variation conferring enhanced photoperiod and flowering traits. Genetic variants in the florigen pathway can provide both environmental flexibility and improved yields. SNPs associated with length of growing season and tolerance to abiotic stresses (precipitation, high temperature) are valuable resources for accelerating breeding for drought-prone environments. Both genomic selection and genome editing can also harness allelic diversity and increase productivity by improving multiple traits, including phenology, plant architecture, yield potential and adaptation to abiotic stresses. Discovering rare alleles and useful haplotypes also provides opportunities to enhance abiotic stress adaptation, while epigenetic variation has potential to enhance abiotic stress adaptation and productivity in crops. By reviewing current knowledge on specific traits and their genetic basis, we highlight recent developments in the understanding of crop functional diversity and identify potential candidate genes for future use. The storage and integration of genetic, genomic and phenotypic information will play an important role in ensuring broad and rapid application of novel genetic discoveries by the plant breeding community. Exploiting alleles for yield-related traits would allow improvement of selection efficiency and overall genetic gain of multigenic traits. An integrated approach involving multiple stakeholders specializing in management and utilization of genetic resources, crop breeding, molecular biology and genomics, agronomy, stress tolerance, and reproductive/seed biology will help to address the global challenge of ensuring food security in the face of growing resource demands and climate change induced stresses.

From plant genomes to phenotypes

Recent advances in sequencing technologies have greatly accelerated the rate of plant genome and applied breeding research. Despite this advancing trend, plant genomes continue to present numerous difficulties to the standard tools and pipelines not only for genome assembly but also gene annotation and downstream analysis. Here we give a perspective on tools, resources and services necessary to assemble and analyze plant genomes and link them to plant phenotypes.

Exploiting the great potential of Sequence Capture data by a new tool, SUPER-CAP

The recent development of Sequence Capture methodology represents a powerful strategy for enhancing data generation to assess genetic variation of targeted genomic regions. Here, we present SUPER-CAP, a bioinformatics web tool aimed at handling Sequence Capture data, fine calculating the allele frequency of variations and building genotype-specific sequence of captured genes. The dataset used to develop this in silico strategy consists of 378 loci and related regulative regions in a collection of 44 tomato landraces. About 14,000 high-quality variants were identified. The high depth (>40×) of coverage and adopting the correct filtering criteria allowed identification of about 4,000 rare variants and 10 genes with a different copy number variation. We also show that the tool is capable to reconstruct genotype-specific sequences for each genotype by using the detected variants. This allows evaluating the combined effect of multiple variants in the same protein. The architecture and functionality of SUPER-CAP makes the software appropriate for a broad set of analyses including SNP discovery and mining. Its functionality, together with the capability to process large data sets and efficient detection of sequence variation, makes SUPER-CAP a valuable bioinformatics tool for genomics and breeding purposes.

High-Throughput Resequencing of Maize Landraces at Genomic Regions Associated with Flowering Time

Despite the reduction in the price of sequencing, it remains expensive to sequence and assemble whole, complex genomes of multiple samples for population studies, particularly for large genomes like those of many crop species. Enrichment of target genome regions coupled with next generation sequencing is a cost-effective strategy to obtain sequence information for loci of interest across many individuals, providing a less expensive approach to evaluating sequence variation at the population scale. Here we evaluate amplicon-based enrichment coupled with semiconductor sequencing on a validation set consisting of three maize inbred lines, two hybrids and 19 landrace accessions. We report the use of a multiplexed panel of 319 PCR assays that target 20 candidate loci associated with photoperiod sensitivity in maize while requiring 25 ng or less of starting DNA per sample. Enriched regions had an average on-target sequence read depth of 105 with 98% of the sequence data mapping to the maize ‘B73’ reference and 80% of the reads mapping to the target interval. Sequence reads were aligned to B73 and 1,486 and 1,244 variants were called using SAMtools and GATK, respectively. Of the variants called by both SAMtools and GATK, 30% were not previously reported in maize. Due to the high sequence read depth, heterozygote genotypes could be called with at least 92.5% accuracy in hybrid materials using GATK. The genetic data are congruent with previous reports of high total genetic diversity and substantial population differentiation among maize landraces. In conclusion, semiconductor sequencing of highly multiplexed PCR reactions is a cost-effective strategy for resequencing targeted genomic loci in diverse maize materials.

From Genomes to GENE-omes: Exome Sequencing Concept and Applications in Crop Improvement

Exome sequencing represents targeted capture and sequencing of 1-2% of 'high-value genomic regions' (subset of the genome) which are enriched for functional variants and harbors low level of repetitive regions. We discuss here an overview of exome sequencing, ways to approach plant exomes, and advantages and applicability of this powerful approach in deciphering functional regions of genomes. Though initially this approach was developed as an alternative to whole genome sequencing (WGS), but the multitude of benefits conferred by sequence capture via hybridization approaches created a niche for itself to solve many of biological riddles, particularly for resolving phylogenetic distances. The technique has also proved to be successful in understanding the basis of natural and induced molecular variation, marker development and developing genomic resources for complex, wild and non-model species, which are still intractable for WGS efforts. Thus, with profound applications of this powerful sequencing strategy, near future is expected to witness a collective expansion of both techniques, i.e., sequence capture via hybridization for evolutionary and ecological research and WGS approaches for its universal accessibility.

Sequence capture by hybridization to explore modern and ancient genomic diversity in model and nonmodel organisms

The recent expansion of next-generation sequencing has significantly improved biological research. Nevertheless, deep exploration of genomes or metagenomic samples remains difficult because of the sequencing depth and the associated costs required. Therefore, different partitioning strategies have been developed to sequence informative subsets of studied genomes. Among these strategies, hybridization capture has proven to be an innovative and efficient tool for targeting and enriching specific biomarkers in complex DNA mixtures. It has been successfully applied in numerous areas of biology, such as exome resequencing for the identification of mutations underlying Mendelian or complex diseases and cancers, and its usefulness has been demonstrated in the agronomic field through the linking of genetic variants to agricultural phenotypic traits of interest. Moreover, hybridization capture has provided access to underexplored, but relevant fractions of genomes through its ability to enrich defined targets and their flanking regions. Finally, on the basis of restricted genomic information, this method has also allowed the expansion of knowledge of nonreference species and ancient genomes and provided a better understanding of metagenomic samples. In this review, we present the major advances and discoveries permitted by hybridization capture and highlight the potency of this approach in all areas of biology.

Genetic Divergence between Camellia sinensis and Its Wild Relatives Revealed via Genome-Wide SNPs from RAD Sequencing

Tea is one of the most popular beverages across the world and is made exclusively from cultivars of Camellia sinensis. Many wild relatives of the genus Camellia that are closely related to C. sinensis are native to Southwest China. In this study, we first identified the distinct genetic divergence between C. sinensis and its wild relatives and provided a glimpse into the artificial selection of tea plants at a genome-wide level by analyzing 15,444 genomic SNPs that were identified from 18 cultivated and wild tea accessions using a high-throughput genome-wide restriction site-associated DNA sequencing (RAD-Seq) approach. Six distinct clusters were detected by phylogeny inferrence and principal component and genetic structural analyses, and these clusters corresponded to six Camellia species/varieties. Genetic divergence apparently indicated that C. taliensis var. bangwei is a semi-wild or transient landrace occupying a phylogenetic position between those wild and cultivated tea plants. Cultivated accessions exhibited greater heterozygosity than wild accessions, with the exception of C. taliensis var. bangwei. Thirteen genes with non-synonymous SNPs exhibited strong selective signals that were suggestive of putative artificial selective footprints for tea plants during domestication. The genome-wide SNPs provide a fundamental data resource for assessing genetic relationships, characterizing complex traits, comparing heterozygosity and analyzing putatitve artificial selection in tea plants.

Species-wide genome sequence and nucleotide polymorphisms from the model allopolyploid plant Brassica napus

Brassica napus (oilseed rape, canola) is one of the world's most important sources of vegetable oil for human nutrition and biofuel, and also a model species for studies investigating the evolutionary consequences of polyploidisation. Strong bottlenecks during its recent origin from interspecific hybridisation, and subsequently through intensive artificial selection, have severely depleted the genetic diversity available for breeding. On the other hand, high-throughput genome profiling technologies today provide unprecedented scope to identify, characterise and utilise genetic diversity in primary and secondary crop gene pools. Such methods also enable implementation of genomic selection strategies to accelerate breeding progress. The key prerequisite is availability of high-quality sequence data and identification of high-quality, genome-wide sequence polymorphisms representing relevant gene pools. We present comprehensive genome resequencing data from a panel of 52 highly diverse natural and synthetic B. napus accessions, along with a stringently selected panel of 4.3 million high-confidence, genome-wide SNPs. The data is of great interest for genomics-assisted breeding and for evolutionary studies on the origins and consequences in allopolyploidisation in plants.