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We report a chromosome-scale assembly and analysis of the Daucus carota genome, an important source of provitamin A in the human diet and the first sequenced genome among members of the Euasterid II clade. We characterized two new polyploidization events, both occurring after the divergence of carrot from members of the Euasterid I clade, clarifying the evolutionary scenario before and after the radiation of the two main Asterid clades. Large- and small-scale lineage-specific duplications contributed to the expansion of gene families including those with roles in flowering time, defense response, flavor, and pigment accumulation. We demonstrated that the primary genetic locus underlying carotenoid accumulation in the carrot root, that is the foundation of the orange color of modern carrots, is not directly controlled at the biosynthetic level. A candidate gene was identified, and transcriptome data suggested that high carotenoid accumulation involves overexpression of several light-induced genes operating in photosystem development and function. These results provide a resource for crop improvement, for comparative genome analysis in the Asterid lineage, and for the discovery of novel genetic mechanisms regulating carotene biosynthesis and accumulation in plants.

Computational tool-assisted primer design for real-time reverse transcription (RT) PCR (qPCR) analysis largely ignores the sequence similarities between sequences of homologous genes in a plant genome. It can lead to false confidence in the quality of the designed primers, which sometimes results in skipping the optimization steps for qPCR. However, the optimization of qPCR parameters plays an essential role in the efficiency, specificity, and sensitivity of each gene’s primers. Here, we proposed an optimized approach to sequentially optimizing primer sequences, annealing temperatures, primer concentrations, and cDNA concentration range for each reference (and target) gene. Our approach started with a sequence-specific primer design that should be based on the single-nucleotide polymorphisms (SNPs) present in all the homologous sequences for each of the reference (and target) genes under study. By combining the efficiency calibrated and standard curve methods with the 2−ΔΔCt method, the standard cDNA concentration curve with a logarithmic scale was obtained for each primer pair for each gene. As a result, an R2 ≥ 0.9999 and the efficiency (E) = 100 ± 5% should be achieved for the best primer pair of each gene, which serve as the prerequisite for using the 2−ΔΔCt method for data analysis. We applied our newly developed approach to identify the best reference genes in different tissues and at various inflorescence developmental stages of Tripidium ravennae, an ornamental and biomass grass, and validated their utility under varying abiotic stress conditions. We also applied this approach to test the expression stability of six reference genes in soybean under biotic stress treatment with Xanthomonas axonopodis pv. glycines (Xag). Thus, these case studies demonstrated the effectiveness of our optimized protocol for qPCR analysis.

Background Among next generation sequence technologies, platforms such as Illumina and SOLiD produce short reads but with higher coverage and lower cost per sequenced nucleotide than 454 or Sanger. A challenge now is to develop efficient strategies to use short-read length platforms for de novo assembly and marker development. The scope of this study was to develop a de novo assembly of carrot ESTs from multiple genotypes using the Illumina platform, and to identify polymorphisms. Results A de novo assembly of transcriptome sequence from four genetic backgrounds produced 58,751 contigs and singletons. Over 50% of these assembled sequences were annotated allowing detection of transposable elements and new carrot anthocyanin genes. Presence of multiple genetic backgrounds in our assembly allowed the identification of 114 computationally polymorphic SSRs, and 20,058 SNPs at a depth of coverage of 20× or more. Polymorphisms were predominantly between inbred lines except for the cultivated x wild RIL pool which had high intra-sample polymorphism. About 90% and 88% of tested SSR and SNP primers amplified a product, of which 70% and 46%, respectively, were of the expected size. Out of verified SSR and SNP markers 84% and 82% were polymorphic. About 25% of SNPs genotyped were polymorphic in two diverse mapping populations. Conclusions This study confirmed the potential of short read platforms for de novo EST assembly and identification of genetic polymorphisms in carrot. In addition we produced the first large-scale transcriptome of carrot, a species lacking genomic resources.

Size and shape are important properties of shrub crops such as blueberries, and they can be particularly useful for evaluating bush architecture suited to mechanical harvesting. The overall goal of this study was to develop a 3D imaging approach to measure size-related traits and bush shape that are relevant to mechanical harvesting. 3D point clouds were acquired for 367 bushes from five genotype groups. Point cloud data were preprocessed to obtain clean bush points for characterizing bush architecture, including bush morphology (height, width, and volume), crown size, and shape descriptors (path curve λ and five shape indices). One-dimensional traits (height, width, and crown size) had high correlations ( R 2  = 0.88–0.95) between proposed method and manual measurements, whereas bush volume showed relatively lower correlations ( R 2  = 0.78–0.85). These correlations suggested that the present approach was accurate in measuring one-dimensional size traits and acceptable in estimating three-dimensional bush volume. Statistical results demonstrated that the five genotype groups were statistically different in crown size and bush shape. The differences matched with human evaluation regarding optimal bush architecture for mechanical harvesting. In particular, a visualization tool could be generated using crown size and path curve λ , which showed great potential of determining bush architecture suitable for mechanical harvesting quickly. Therefore, the processing pipeline of 3D point cloud data presented in this study is an effective tool for blueberry breeding programs (in particular for mechanical harvesting) and farm management. Crop breeding: 3D measurement of blueberry bush shape Researchers in the United States have developed a 3D imaging technique to quantitatively measure the shape of blueberry bushes in order to evaluate their suitability for mechanical harvesting. The team, led by Changying Li of the University of Georgia, used handheld LiDAR scanners to collect 3D data from bushes in blueberry fields. Their analysis pipeline converted these data into a description of the bushes, including height, width, volume, crown size, and parameters describing the shape. While some traits matched manual measurements better than others, the analysis described bush shape sufficiently to distinguish varieties. The team also created a tool to visualize key parameters related to suitability for mechanical harvesting. This study provides a promising tool to evaluate and manage varieties of blueberries and similar crops, though further work is needed to speed up data collection.

The widely cultivated pepper, Capsicum spp., important as a vegetable and spice crop world-wide, is one of the most diverse crops. To enhance breeding programs, a detailed characterization of Capsicum diversity including morphological, geographical and molecular data is required. Currently, molecular data characterizing Capsicum genetic diversity is limited. The development and application of high-throughput genome-wide markers in Capsicum will facilitate more detailed molecular characterization of germplasm collections, genetic relationships, and the generation of ultra-high density maps. We have developed the Pepper GeneChip® array from Affymetrix for polymorphism detection and expression analysis in Capsicum. Probes on the array were designed from 30,815 unigenes assembled from expressed sequence tags (ESTs). Our array design provides a maximum redundancy of 13 probes per base pair position allowing integration of multiple hybridization values per position to detect single position polymorphism (SPP). Hybridization of genomic DNA from 40 diverse C. annuum lines, used in breeding and research programs, and a representative from three additional cultivated species (C. frutescens, C. chinense and C. pubescens) detected 33,401 SPP markers within 13,323 unigenes. Among the C. annuum lines, 6,426 SPPs covering 3,818 unigenes were identified. An estimated three-fold reduction in diversity was detected in non-pungent compared with pungent lines, however, we were able to detect 251 highly informative markers across these C. annuum lines. In addition, an 8.7 cM region without polymorphism was detected around Pun1 in non-pungent C. annuum. An analysis of genetic relatedness and diversity using the software Structure revealed clustering of the germplasm which was confirmed with statistical support by principle components analysis (PCA) and phylogenetic analysis. This research demonstrates the effectiveness of parallel high-throughput discovery and application of genome-wide transcript-based markers to assess genetic and genomic features among Capsicum annuum.

Blackberry ( subgenus ) is a soft-fruited specialty crop that often suffers economic losses due to degradation in the shipping process. During transportation, fresh-market blackberries commonly leak, decay, deform, or become discolored through a disorder known as red drupelet reversion (RDR). Over the past 50 years, breeding programs have achieved better fruit firmness and postharvest quality through traditional selection methods, but the underlying genetic variation is poorly understood. We conducted a genome-wide association of fruit firmness and RDR measured in 300 tetraploid fresh-market blackberry genotypes from 2019-2021 with 65,995 SNPs concentrated in genic regions of the reference genome. Fruit firmness and RDR had entry-mean broad sense heritabilities of 68% and 34%, respectively. Three variants on homologs of polygalacturonase (PG), pectin methylesterase (PME), and glucan endo-1,3-β-glucosidase explained 27% of variance in fruit firmness and were located on chromosomes Ra06, Ra01, and Ra02, respectively. Another PG homolog variant on chromosome Ra02 explained 8% of variance in RDR, but it was in strong linkage disequilibrium with 212 other RDR-associated SNPs across a 23 Mb region. A large cluster of six PME and PME inhibitor homologs was located near the fruit firmness quantitative trait locus (QTL) identified on Ra01. RDR and fruit firmness shared a significant negative correlation ( = -0.28) and overlapping QTL regions on Ra02 in this study. Our work demonstrates the complex nature of postharvest quality traits in blackberry, which are likely controlled by many small-effect QTLs. This study is the first large-scale effort to map the genetic control of quantitative traits in blackberry and provides a strong framework for future GWAS. Phenotypic and genotypic datasets may be used to train genomic selection models that target the improvement of postharvest quality.

Background Tripidium ravennae is a cold-hardy, diploid species in the sugarcane complex ( Poaceae subtribe Saccharinae ) with considerable potential as a genetic resource for developing improved bioenergy and ornamental grasses. An improved understanding of the genetic regulation of reproductive processes (e.g., floral induction, inflorescence development, and seed development) will enable future applications of precision breeding and gene editing of floral and seed development. In particular, the ability to silence reproductive processes would allow for developing seedless forms of valuable but potentially invasive plants. The objective of this research was to characterize the gene expression environment of reproductive development in T. ravennae. Results During the early phases of inflorescence development, multiple key canonical floral integrators and pathways were identified. Annotations of type II subfamily of MADS-box transcription factors, in particular, were over-represented in the GO enrichment analyses and tests for differential expression (FDR p -value < 0.05). The differential expression of floral integrators observed in the early phases of inflorescence development diminished prior to inflorescence determinacy regulation. Differential expression analysis did not identify many unique genes at mid-inflorescence development stages, though typical biological processes involved in plant growth and development expressed abundantly. The increase in inflorescence determinacy regulatory elements and putative homeotic floral development unigenes at mid-inflorescence development coincided with the expression of multiple meiosis annotations and multicellular organism developmental processes. Analysis of seed development identified multiple unigenes involved in oxidative-reductive processes. Conclusion Reproduction in grasses is a dynamic system involving the sequential coordination of complex gene regulatory networks and developmental processes. This research identified differentially expressed transcripts associated with floral induction, inflorescence development, and seed development in T. ravennae . These results provide insights into the molecular regulation of reproductive development and provide a foundation for future investigations and analyses, including genome annotation, functional genomics characterization, gene family evolutionary studies, comparative genomics, and precision breeding.

Background Molecular breeding of pepper ( Capsicum spp. ) can be accelerated by developing DNA markers associated with transcriptomes in breeding germplasm. Before the advent of next generation sequencing (NGS) technologies, the majority of sequencing data were generated by the Sanger sequencing method. By leveraging Sanger EST data, we have generated a wealth of genetic information for pepper including thousands of SNPs and Single Position Polymorphic (SPP) markers. To complement and enhance these resources, we applied NGS to three pepper genotypes: Maor, Early Jalapeño and Criollo de Morelos-334 (CM334) to identify SNPs and SSRs in the assembly of these three genotypes. Results Two pepper transcriptome assemblies were developed with different purposes. The first reference sequence, assembled by CAP3 software, comprises 31,196 contigs from >125,000 Sanger-EST sequences that were mainly derived from a Korean F 1 -hybrid line, Bukang. Overlapping probes were designed for 30,815 unigenes to construct a pepper Affymetrix GeneChip® microarray for whole genome analyses. In addition, custom Python scripts were used to identify 4,236 SNPs in contigs of the assembly. A total of 2,489 simple sequence repeats (SSRs) were identified from the assembly, and primers were designed for the SSRs. Annotation of contigs using Blast2GO software resulted in information for 60% of the unigenes in the assembly. The second transcriptome assembly was constructed from more than 200 million Illumina Genome Analyzer II reads (80–120 nt) using a combination of Velvet, CLC workbench and CAP3 software packages. BWA, SAMtools and in-house Perl scripts were used to identify SNPs among three pepper genotypes. The SNPs were filtered to be at least 50 bp from any intron-exon junctions as well as flanking SNPs. More than 22,000 high-quality putative SNPs were identified. Using the MISA software, 10,398 SSR markers were also identified within the Illumina transcriptome assembly and primers were designed for the identified markers. The assembly was annotated by Blast2GO and 14,740 (12%) of annotated contigs were associated with functional proteins. Conclusions Before availability of pepper genome sequence, assembling transcriptomes of this economically important crop was required to generate thousands of high-quality molecular markers that could be used in breeding programs. In order to have a better understanding of the assembled sequences and to identify candidate genes underlying QTLs, we annotated the contigs of Sanger-EST and Illumina transcriptome assemblies. These and other information have been curated in a database that we have dedicated for pepper project.

Late blight (LB), caused by the oomycete Phytophthora infestans, is one of the most destructive diseases of the cultivated tomato (Solanum lycopersicum L.) and potato (Solanum tuberosum L.) worldwide. Genetic changes in the pathogen have resulted in the emergence of new genotypes, overcoming formerly effective fungicides or host resistance genes. We previously reported the identification of a LB‐resistant accession (PI 270441) of the wild tomato species S. pimpinellifolium L. and the high heritability of its resistance. In the present study, an F2 population (n = 1,209), derived from a cross between PI 270441 and a LB‐susceptible tomato breeding line (Fla. 8059), was screened for response to LB infection. Extreme resistant (n = 44) and susceptible (n = 39) F2 individuals were selected and used in a trait‐based marker analysis (TBA; a.k.a selective genotyping) to identify and map quantitative trait loci (QTLs) conferring LB resistance. Reduced representation libraries (RRLs) of Fla. 8059 and PI 270441 were constructed, sequenced, and mapped to the tomato genome. A total of 13,054 single‐nucleotide polymorphisms (SNPs) were identified, of which, 200 were used to construct a genetic linkage map and locate QTLs. Four LB resistance QTLs were identified on chromosomes 1, 10, and 11 of PI 270441. The markers associated with these QTLs can be used to transfer LB resistance from PI 270441 into new tomato cultivars and to develop near‐isogenic lines for fine mapping of the QTL. Core Ideas A new source of late blight (LB) resistance in tomato was genetically characterized. New single‐nucleotide polymorphism markers were identified using the genotyping‐by‐sequencing approach. A new genetic map of tomato was developed. New quantitative trait loci conferring LB resistance in tomato were identified.

Fruit quality traits play a significant role in consumer preferences and consumption in blueberry (Vaccinium corymbosum L). The objectives of this study were to construct a high-density linkage map and to identify the underlying genetic basis of fruit quality traits in blueberry. A total of 287 F1 individuals derived from a cross between two southern highbush blueberry cultivars, ‘Reveille’ and ‘Arlen’, were phenotyped over three years (2016–2018) for fruit quality-related traits, including titratable acidity, pH, total soluble solids, and fruit weight. A high-density linkage map was constructed using 17k single nucleotide polymorphisms markers. The linkage map spanned a total of 1397 cM with an average inter-loci distance of 0.08 cM. The quantitative trait loci interval mapping based on the hidden Markov model identified 18 loci for fruit quality traits, including seven loci for fruit weight, three loci for titratable acidity, five loci for pH, and three loci for total soluble solids. Ten of these loci were detected in more than one year. These loci explained phenotypic variance ranging from 7 to 28% for titratable acidity and total soluble solid, and 8–13% for pH. However, the loci identified for fruit weight did not explain more than 10% of the phenotypic variance. We also reported the association between fruit quality traits and metabolites detected by Proton nuclear magnetic resonance analysis directly responsible for these fruit quality traits. Organic acids, citric acid, and quinic acid were significantly (P < 0.05) and positively correlated with titratable acidity. Sugar molecules showed a strong and positive correlation with total soluble solids. Overall, the study dissected the genetic basis of fruit quality traits and established an association between these fruit quality traits and metabolites.