Humira Sonah

An Improved Genotyping by Sequencing (GBS) Approach Offering Increased Versatility and Efficiency of SNP Discovery and Genotyping

Highly parallel SNP genotyping platforms have been developed for some important crop species, but these platforms typically carry a high cost per sample for first-time or small-scale users. In contrast, recently developed genotyping by sequencing (GBS) approaches offer a highly cost effective alternative for simultaneous SNP discovery and genotyping. In the present investigation, we have explored the use of GBS in soybean. In addition to developing a novel analysis pipeline to call SNPs and indels from the resulting sequence reads, we have devised a modified library preparation protocol to alter the degree of complexity reduction. We used a set of eight diverse soybean genotypes to conduct a pilot scale test of the protocol and pipeline. Using ApeKI for GBS library preparation and sequencing on an Illumina GAIIx machine, we obtained 5.5 M reads and these were processed using our pipeline. A total of 10,120 high quality SNPs were obtained and the distribution of these SNPs mirrored closely the distribution of gene-rich regions in the soybean genome. A total of 39.5% of the SNPs were present in genic regions and 52.5% of these were located in the coding sequence. Validation of over 400 genotypes at a set of randomly selected SNPs using Sanger sequencing showed a 98% success rate. We then explored the use of selective primers to achieve a greater complexity reduction during GBS library preparation. The number of SNP calls could be increased by almost 40% and their depth of coverage was more than doubled, thus opening the door to an increase in the throughput and a significant decrease in the per sample cost. The approach to obtain high quality SNPs developed here will be helpful for marker assisted genomics as well as assessment of available genetic resources for effective utilisation in a wide number of species.

Genome-Wide Distribution and Organization of Microsatellites in Plants: An Insight into Marker Development in Brachypodium

Plant genomes are complex and contain large amounts of repetitive DNA including microsatellites that are distributed across entire genomes. Whole genome sequences of several monocot and dicot plants that are available in the public domain provide an opportunity to study the origin, distribution and evolution of microsatellites, and also facilitate the development of new molecular markers. In the present investigation, a genome-wide analysis of microsatellite distribution in monocots (Brachypodium, sorghum and rice) and dicots (Arabidopsis, Medicago and Populus) was performed. A total of 797,863 simple sequence repeats (SSRs) were identified in the whole genome sequences of six plant species. Characterization of these SSRs revealed that mono-nucleotide repeats were the most abundant repeats, and that the frequency of repeats decreased with increase in motif length both in monocots and dicots. However, the frequency of SSRs was higher in dicots than in monocots both for nuclear and chloroplast genomes. Interestingly, GC-rich repeats were the dominant repeats only in monocots, with the majority of them being present in the coding region. These coding GC-rich repeats were found to be involved in different biological processes, predominantly binding activities. In addition, a set of 22,879 SSR markers that were validated by e-PCR were developed and mapped on different chromosomes in Brachypodium for the first time, with a frequency of 101 SSR markers per Mb. Experimental validation of 55 markers showed successful amplification of 80% SSR markers in 16 Brachypodium accessions. An online database ‘BraMi’ (Brachypodium microsatellite markers) of these genome-wide SSR markers was developed and made available in the public domain. The observed differential patterns of SSR marker distribution would be useful for studying microsatellite evolution in a monocot–dicot system. SSR markers developed in this study would be helpful for genomic studies in Brachypodium and related grass species, especially for the map based cloning of the candidate gene(s).

Identification of loci governing eight agronomic traits using a GBS-GWAS approach and validation by QTL mapping in soya bean

Soya bean is a major source of edible oil and protein for human consumption as well as animal feed. Understanding the genetic basis of different traits in soya bean will provide important insights for improving breeding strategies for this crop. A genome-wide association study (GWAS) was conducted to accelerate molecular breeding for the improvement of agronomic traits in soya bean. A genotyping-by-sequencing (GBS) approach was used to provide dense genome-wide marker coverage (>47,000 SNPs) for a panel of 304 short-season soya bean lines. A subset of 139 lines, representative of the diversity among these, was characterized phenotypically for eight traits under six environments (3 sites × 2 years). Marker coverage proved sufficient to ensure highly significant associations between the genes known to control simple traits (flower, hilum and pubescence colour) and flanking SNPs. Between one and eight genomic loci associated with more complex traits (maturity, plant height, seed weight, seed oil and protein) were also identified. Importantly, most of these GWAS loci were located within genomic regions identified by previously reported quantitative trait locus (QTL) for these traits. In some cases, the reported QTLs were also successfully validated by additional QTL mapping in a biparental population. This study demonstrates that integrating GBS and GWAS can be used as a powerful complementary approach to classical biparental mapping for dissecting complex traits in soya bean.

Identification of major quantitative trait loci qSBR11-1 for sheath blight resistance in rice

Sheath blight caused by Rhizoctonia solani Kühn is one of the important diseases of rice, resulting in heavy yield loss in rice every year. No rice line resistant to sheath blight has been identified till date. However, in some rice lines a high degree of resistance to R. solani has been observed. An indica rice line, Tetep, is a well documented source of durable and broad spectrum resistance to rice blast as well as quantitative resistance to sheath blight. The present study identified genetic loci for quantitative resistance to sheath blight in rice line Tetep. A mapping population consisting of 127 recombinant inbred lines derived from a cross between rice cultivars HP2216 (susceptible) and Tetep (resistant to sheath blight) was evaluated for sheath blight resistance and other agronomic traits for 4xa0years across three locations. Based on sheath blight phenotypes and genetic map with 126 evenly distributed molecular markers, a quantitative trait loci (QTLs) contributing to sheath blight resistance was identified on long arm of chromosome 11. Two QTL mapping approaches i.e., single marker analysis and composite interval mapping in multi environments were used to identify QTLs for sheath blight resistance and agronomical traits. The QTL qSBR11-1 for sheath blight resistance was identified between the marker interval RM1233 (26.45xa0Mb) to sbq33 (28.35xa0Mb) on chromosome 11. This region was further narrowed down to marker interval K39516 to sbq33 (~0.85xa0Mb) and a total of 154 genes were predicted including 11 tandem repeats of chitinase genes which may be responsible for sheath blight resistance in rice line Tetep. A set of 96 varieties and a F2 population were used for validation of markers linked to the QTL region. The results indicate that there is very high genetic variation among varieties at this locus, which can serve as a starting point for allele mining of sheath blight resistance.

Genome wide association mapping of Sclerotinia sclerotiorum resistance in soybean with a genotyping by sequencing approach

Sclerotinia stem rot (SSR) is one of the most important pests in cool soybean growing regions of the Northeastern United States and Canada. However, the intensity of infestations varies considerably from year to year according to weather conditions, thus making it difficult for breeders to select under uniform disease pressure. Selection for resistance to SSR would be greatly facilitated by the use of molecular markers. In this work, a collection of 130 lines was inoculated using the cotton pad method and was genetically characterized using a genotyping‐by‐sequencing (GBS) protocol optimized for soybean. Genome‐wide association mapping (AM) and linkage disequilibrium (LD) analyses were performed with 7864 single nucleotide polymorphisms (SNPs). Linkage disequilibrium varied considerably over physical distance, reaching a r2 value of 0.2 after 8.5 Mb in the pericentromeric region and 0.5 Mb in the telomeric region. The mixed linear model (MLM) performed very well in accounting for population structure and relatedness, as only 5.5% of the observed p‐values were < 0.05. The strongest association was found on chromosome Gm15 (p‐value = 1.38 × 10–6; q‐value [adjusted p‐value] = 0.011). Two additional SNP markers in the vicinity had a q‐value < 0.1. This marker was validated in the progeny of a biparental cross, where F4:6 lines carrying the susceptibility allele developed lesions 17.6 mm longer than lines carrying the resistance allele. Interestingly, other genes contributing to resistance to pathogens have been reported in this region of Gm15. Three other association peaks having a q‐value < 0.1 were detected on chromosomes Gm01, Gm19, and Gm20.

Integrating omic approaches for abiotic stress tolerance in soybean

Soybean production is greatly influenced by abiotic stresses imposed by environmental factors such as drought, water submergence, salt, and heavy metals. A thorough understanding of plant response to abiotic stress at the molecular level is a prerequisite for its effective management. The molecular mechanism of stress tolerance is complex and requires information at the omic level to understand it effectively. In this regard, enormous progress has been made in the omics field in the areas of genomics, transcriptomics, and proteomics. The emerging field of ionomics is also being employed for investigating abiotic stress tolerance in soybean. Omic approaches generate a huge amount of data, and adequate advancements in computational tools have been achieved for effective analysis. However, the integration of omic-scale information to address complex genetics and physiological questions is still a challenge. In this review, we have described advances in omic tools in the view of conventional and modern approaches being used to dissect abiotic stress tolerance in soybean. Emphasis was given to approaches such as quantitative trait loci (QTL) mapping, genome-wide association studies (GWAS), and genomic selection (GS). Comparative genomics and candidate gene approaches are also discussed considering identification of potential genomic loci, genes, and biochemical pathways involved in stress tolerance mechanism in soybean. This review also provides a comprehensive catalog of available online omic resources for soybean and its effective utilization. We have also addressed the significance of phenomics in the integrated approaches and recognized high-throughput multi-dimensional phenotyping as a major limiting factor for the improvement of abiotic stress tolerance in soybean.

Identification and functional characterization of silicon transporters in soybean using comparative genomics of major intrinsic proteins in Arabidopsis and rice

Silicon (Si) confers several benefits to many plant species when absorbed as silicic acid through nodulin 26-like intrinsic proteins (NIPs). The NIPs belong to major intrinsic protein (MIP) family, members of which form channels with high selectivity to control transport of water and different solutes. Here, comparative genomic analysis of the MIPs was performed to investigate the presence of Si transporter MIPs in soybean. Thorough analysis of phylogeny, gene organization, transcriptome profiling and protein modeling was performed to characterize MIPs in rice, Arabidopsis and soybean. Based on several attributes, two putative Si transporter genes, GmNIP2-1 and GmNIP2-2, were identified, characterized and cloned from soybean. Expression of both genes was detected in shoot and root tissues, and decreased as Si increased. The protein encoded by GmNIP2-2 showed functionality for Si transport when expressed in Xenopus oocytes, thus confirming the genetic capability of soybean to absorb the element. Comparative analysis of MIPs in plants provides opportunities to decipher gene evolution, functionality and selectivity of nutrient uptake mechanisms. Exploitation of this strategy has helped to uncover unique features of MIPs in soybean. The identification and functional characterization of Si transporters can be exploited to optimize the benefits that plants can derive from Si absorption.

Soybean (Glycine max) SWEET gene family: insights through comparative genomics, transcriptome profiling and whole genome re-sequence analysis

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.

A precise spacing between the NPA domains of aquaporins is essential for silicon permeability in plants.

The controversy surrounding silicon (Si) benefits and essentiality in plants is exacerbated by the differential ability of species to absorb this element. This property is seemingly enhanced in species carrying specific nodulin 26-like intrinsic proteins (NIPs), a subclass of aquaporins. In this work, our aim was to characterize plant aquaporins to define the features that confer Si permeability. Through comparative analysis of 985 aquaporins in 25 species with differing abilities to absorb Si, we were able to predict 30 Si transporters and discovered that Si absorption is exclusively confined to species that possess NIP-III aquaporins with a GSGR selectivity filter and a precise distance of 108 amino acids (AA) between the asparagine-proline-alanine (NPA) domains. The latter feature is of particular significance since it had never been reported to be essential for Si selectivity. Functionality assessed in the Xenopus oocyte expression system showed that NIPs with 108 AA spacing exhibited Si permeability, while proteins differing in that distance did not. In subsequent functional studies, a Si transporter from poplar mutated into variants with 109- or 107-AA spacing failed to import, and a tomato NIP gene mutated from 109 to 108 AA exhibited a rare gain of function. These results provide a precise molecular basis to classify higher plants into Si accumulators or excluders.

Genomic resources in horticultural crops: Status, utility and challenges

A significant review of status and availability of genomic resources in horticultural crops can be utilized for the efficient exploitation of the current research in developing improved varieties and also defining future goals. In this review, we describe the current genomic resources available in major horticultural crops and utility of the genomic and genic sequence information for isolating and characterizing novel useful genes and designing new DNA markers. We have found that these genomic resources have been utilized for both basic and applied research; however the progress is relatively slow. Recent advances in automation and high throughput techniques used in decoding plant genomes play an important role to speed up the genomic research. With the establishment of genome and transcriptome sequencing projects for several horticultural crops, huge wealth of sequence information have been generated. These sequence information have been used extensively for analyzing and understanding genome structures and complexities, comparative and functional genomics and to mine useful genes and molecular markers. However, certain limitations present a number of challenges for the generation and utilization of genomic resources in many important crops.