Soil salinity is a limiting factor of crop yield. The soybean is sensitive to soil salinity, and a dominant gene, Glyma03g32900 is primarily responsible for salt-tolerance. The identification of high throughput and robust markers as well as the deployment of salt-tolerant cultivars are effective approaches to minimize yield loss under saline conditions. We utilized high quality (15x) whole-genome resequencing (WGRS) on 106 diverse soybean lines and identified three major structural variants and allelic variation in the promoter and genic regions of the GmCHX1 gene. The discovery of single nucleotide polymorphisms (SNPs) associated with structural variants facilitated the design of six KASPar assays. Additionally, haplotype analysis and pedigree tracking of 93 U.S. ancestral lines were performed using publically available WGRS datasets. Identified SNP markers were validated, and a strong correlation was observed between the genotype and salt treatment phenotype (leaf scorch, chlorophyll content and Na+ accumulation) using a panel of 104 soybean lines and, an interspecific bi-parental population (F8) from PI483463 x Hutcheson. These markers precisely identified salt-tolerant/sensitive genotypes (>91%), and different structural-variants (>98%). These SNP assays, supported by accurate phenotyping, haplotype analyses and pedigree tracking information, will accelerate marker-assisted selection programs to enhance the development of salt-tolerant soybean cultivars.

BackgroundSWEET (MtN3_saliva) domain proteins, a recently identified group of efflux transporters, play an indispensable role in sugar efflux, phloem loading, plant-pathogen interaction and reproductive tissue development. The SWEET gene family is predominantly studied in Arabidopsis and members of the family are being investigated in rice. To date, no transcriptome or genomics analysis of soybean SWEET genes has been reported.ResultsIn the present investigation, we explored the evolutionary aspect of the SWEET gene family in diverse plant species including primitive single cell algae to angiosperms with a major emphasis on Glycine max. Evolutionary features showed expansion and duplication of the SWEET gene family in land plants. Homology searches with BLAST tools and Hidden Markov Model-directed sequence alignments identified 52 SWEET genes that were mapped to 15 chromosomes in the soybean genome as tandem duplication events. Soybean SWEET (GmSWEET) genes showed a wide range of expression profiles in different tissues and developmental stages. Analysis of public transcriptome data and expression profiling using quantitative real time PCR (qRT-PCR) showed that a majority of the GmSWEET genes were confined to reproductive tissue development. Several natural genetic variants (non-synonymous SNPs, premature stop codons and haplotype) were identified in the GmSWEET genes using whole genome re-sequencing data analysis of 106 soybean genotypes. A significant association was observed between SNP-haplogroup and seed sucrose content in three gene clusters on chromosome 6.ConclusionPresent investigation utilized comparative genomics, transcriptome profiling and whole genome re-sequencing approaches and provided a systematic description of soybean SWEET genes and identified putative candidates with probable roles in the reproductive tissue development. Gene expression profiling at different developmental stages and genomic variation data will aid as an important resource for the soybean research community and can be extremely valuable for understanding sink unloading and enhancing carbohydrate delivery to developing seeds for improving yield.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-015-1730-y) contains supplementary material, which is available to authorized users.

Food resources of the modern world are strained due to the increasing population. There is an urgent need for innovative methods and approaches to augment food production. Legume seeds are major resources of human food and animal feed with their unique nutrient compositions including oil, protein, carbohydrates, and other beneficial nutrients. Recent advances in next-generation sequencing (NGS) together with “omics” technologies have considerably strengthened soybean research. The availability of well annotated soybean genome sequence along with hundreds of identified quantitative trait loci (QTL) associated with different seed traits can be used for gene discovery and molecular marker development for breeding applications. Despite the remarkable progress in these technologies, the analysis and mining of existing seed genomics data are still challenging due to the complexity of genetic inheritance, metabolic partitioning, and developmental regulations. Integration of “omics tools” is an effective strategy to discover key regulators of various seed traits. In this review, recent advances in “omics” approaches and their use in soybean seed trait investigations are presented along with the available databases and technological platforms and their applicability in the improvement of soybean. This article also highlights the use of modern breeding approaches, such as genome-wide association studies (GWAS), genomic selection (GS), and marker-assisted recurrent selection (MARS) for developing superior cultivars. A catalog of available important resources for major seed composition traits, such as seed oil, protein, carbohydrates, and yield traits are provided to improve the knowledge base and future utilization of this information in the soybean crop improvement programs.

Induced mutagenesis is one of the most effective strategies for trait improvement without altering the well-optimized genetic background of the cultivars. In this review, several currently accessible methods such as physical, chemical and insertional mutagenesis have been discussed concerning their efficient exploration for the tomato crop improvement. Similarly, challenges for the adaptation of genome-editing, a newly developed technique providing an opportunity to induce precise mutation, have been addressed. Several efforts of genome-editing have been demonstrated in tomato and other crops, exploring its effectiveness and convenience for crop improvement. Descriptive data compiled here from such efforts will be helpful for the efficient exploration of technological advances. However, uncertainty about the regulation of genome-edited crops is still a significant concern, particularly when timely trait improvement in tomato cultivars is needed. In this regard, random approaches of induced mutagenesis are still promising if efficiently explored in breeding applications. Precise identification of casual mutation is a prerequisite for the molecular understanding of the trait development as well as its utilization for the breeding program. Recent advances in sequencing techniques provide an opportunity for the precise detection of mutagenesis-induced sequence variations at a large scale in the genome. Here, we reviewed several novel next-generation sequencing based mutation mapping approaches including Mutmap, MutChromeSeq, and whole-genome sequencing-based mapping which has enormous potential to accelerate the mutation breeding in tomato. The proper utilization of the existing well-characterized tomato mutant resources combined with novel mapping approaches would inevitably lead to rapid enhancement of tomato quality and yield. This article provides an overview of the principles and applications of mutagenesis approaches in tomato and discusses the current progress and challenges involved in tomato mutagenesis research.

Induced mutagenesis is one of the most efficient tools that has been utilized extensively to create genetic variation as well as for identification of key regulatory genes for economically important traits toward the crop improvement. Mutations can be induced by several techniques such as physical, chemical, and insertional mutagen treatments; however, these methods are not preferred because of cost and tedious process. Nonetheless, with the advancements in next-generation sequencing (NGS) techniques, millions of mutations can be detected in a very short period of time and, therefore, considered as convenient and cost efficient. Furthermore, induced mutagenesis coupled with whole-genome sequencing has provided a robust platform for forward and reverse genetic applications. Moreover, the availability of whole-genome sequence information for large number of crops has enabled target-specific genome editing techniques as a preferable method to engineer desired mutations. The available genome editing approaches such as ZFNs (Zinc Finger Nucleases), transcription activator like effector nucleases (TALENS), and clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated9 (Cas9) endonuclease have been utilized to perform site-specific mutations in several plant species. In particular, the CRISPR/Cas9 has transformed the genome editing because of its simplicity and robustness, therefore, have been utilized to enhance biotic and abiotic stress resistance. The Special Issue of Plants highlights the efforts by the scientific community utilizing mutagenesis techniques for the identification of novel genes toward crop improvement.

Tomato, one of the most important crops worldwide, has a high demand in the fresh fruit market and processed food industries. Despite having considerably high productivity, continuous supply as per the market demand is hard to achieve, mostly because of periodic losses occurring due to biotic as well as abiotic stresses. Although tomato is a temperate crop, it is grown in almost all the climatic zones because of widespread demand, which makes it challenge to adapt in diverse conditions. Development of tomato cultivars with enhanced abiotic stress tolerance is one of the most sustainable approaches for its successful production. In this regard, efforts are being made to understand the stress tolerance mechanism, gene discovery, and interaction of genetic and environmental factors. Several omics approaches, tools, and resources have already been developed for tomato growing. Modern sequencing technologies have greatly accelerated genomics and transcriptomics studies in tomato. These advancements facilitate Quantitative trait loci (QTL) mapping, genome-wide association studies (GWAS), and genomic selection (GS). However, limited efforts have been made in other omics branches like proteomics, metabolomics, and ionomics. Extensive cataloging of omics resources made here has highlighted the need for integration of omics approaches for efficient utilization of resources and a better understanding of the molecular mechanism. The information provided here will be helpful to understand the plant responses and the genetic regulatory networks involved in abiotic stress tolerance and efficient utilization of omics resources for tomato crop improvement.

Seed composition is one of the most important determinants of the economic values in soybean. The quality and quantity of different seed components, such as oil, protein, and carbohydrates, are crucial ingredients in food, feed, and numerous industrial products. Soybean researchers have successfully developed and utilized a diverse set of molecular markers for seed trait improvement in soybean breeding programs. It is imperative to design and develop molecular assays that are accurate, robust, high-throughput, cost-effective, and available on a common genotyping platform. In the present study, we developed and validated KASP (Kompetitive allele-specific polymerase chain reaction) genotyping assays based on previously known functional mutant alleles for the seed composition traits, including fatty acids, oligosaccharides, trypsin inhibitor, and lipoxygenase. These assays were validated on mutant sources as well as mapping populations and precisely distinguish the homozygotes and heterozygotes of the mutant genes. With the obvious advantages, newly developed KASP assays in this study can substitute the genotyping assays that were previously developed for marker-assisted selection (MAS). The functional gene-based assay resource developed using common genotyping platform will be helpful to accelerate efforts to improve soybean seed composition traits.

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