High-Throughput Sequencing Reveals Single Nucleotide Variants in Longer-Kernel Bread Wheat.
Ontology highlight
ABSTRACT:
SUBMITTER: Chen F
PROVIDER: S-EPMC4976665 | biostudies-literature | 2016
REPOSITORIES: biostudies-literature
Publications
High-Throughput Sequencing Reveals Single Nucleotide Variants in Longer-Kernel Bread Wheat.
Chen Feng F Zhu Zibo Z Zhou Xiaobian X Yan Yan Y Dong Zhongdong Z Cui Dangqun D
Frontiers in plant science 20160808
The transcriptomes of bread wheat Yunong 201 and its ethyl methanesulfonate derivative Yunong 3114 were obtained by next-sequencing technology. Single nucleotide variants (SNVs) in the wheat strains were explored and compared. A total of 5907 and 6287 non-synonymous SNVs were acquired for Yunong 201 and 3114, respectively. A total of 4021 genes with SNVs were obtained. The genes that underwent non-synonymous SNVs were significantly involved in ATP binding, protein phosphorylation, and cellular p ...[more]
Similar Datasets
Project description:TaGS5 genes were cloned from bread wheat and were physically mapped on 3AS and 3DS. Sequencing results revealed that a SNP was found in the sixth exon of TaGS5-A1 gene. The SNP resulted in amino acid change from alanine to serine at the 303 bp position of TaGS5-A1. These two alleles were designated as TaGS5-A1a (alanine at the 303 bp position) and TaGS5-A1b genes (serine at the 303-bp position). Analysis of association of TaGS5-A1 alleles with agronomic traits indicated that cultivars with TaGS5-A1b possessed wider kernel width and higher thousand-kernel weight, as well as significantly lower plant height, spike length, and internode length below spike than those of cultivars with TaGS5-A1a over 3 years. These trait differences between TaGS5-A1a and TaGS5-A1b genotypes were larger in landraces than in modern cultivars. This finding suggested that TaGS5 gene played an important role in modulating yield-related traits in the landraces, which possibly resulted from numerous superior genes gathering in modern cultivars after strong artificial selection. The preferred TaGS5-A1b haplotype underwent very strong positive selection in Chinese modern wheat breeding, but not in Chinese landraces. Expression analysis of the TaGS5-A1 gene indicated that TaGS5-A1b allele possessed significantly higher expression level than TaGS5-A1b allele in differently developmental seeds. This study could provide relatively superior genotype in view of agronomic traits in wheat breeding programs. Likewise, this study could offer important information for the dissection of molecular and genetic basis of yield-related traits.
| S-EPMC4688388 | biostudies-literature
Project description:Forward genetic approaches have limited use for agronomic traits that can't be reliably scored on a single plant basis. Thus, mutants in wheat and other crops are more useful for gene function studies by reverse genetic approach. With a long-term goal to develop a sequence-based mutation detection resource in hexaploid wheat, we conducted a feasibility study to accurately differentiate induced mutations from the homoeologs' sequence variations present among the three wheat genomes.A reduced representation ApeKI library consisting of 21 Ethylmethane Sulfonate (EMS) induced mutants and two wild type cv. Indian plants was developed using individual barcode adapters and sequenced. A novel bioinformatics pipeline was developed to identify sequence variants using 178,464 wheat unigenes as a reference wheat transcriptome. In total, 14,130 mutational changes [Single Nucleotide Polymorphisms (SNPs) and Insertions/Deletions (INDELs)] and 150,511 homoeologous sequence changes were detected. On an average, 662 SNPs (ranging from 46 to 1,330) and 10 small INDELs (ranging from 0 to 23) were identified for each of the mutants. A mutation frequency of one per 5 Kb was observed with 70 % being transitions and 30 % transversions. The pipeline was tested using the known sequence changes in the three wheat genes. Genes present in the distal regions of the chromosomes were found to be more prone to EMS compared to genes present in the proximal regions. Redefined parameters identified a total of 28,348 mutational changes (1,349/plant).We conclude that sequencing based mutation detection is a valuable method to identify induced mutations at large.
| S-EPMC4650848 | biostudies-literature
Project description:BackgroundSingle Nucleotide Polymorphism (SNP) panels recently developed for the assessment of genetic diversity in wheat are primarily based on elite varieties, mostly those of bread wheat. The usefulness of such SNP panels for studying wheat evolution and domestication has not yet been fully explored and ascertainment bias issues can potentially affect their applicability when studying landraces and tetraploid ancestors of bread wheat. We here evaluate whether population structure and evolutionary history can be assessed in tetraploid landrace wheats using SNP markers previously developed for the analysis of elite cultivars of hexaploid wheat.ResultsWe genotyped more than 100 tetraploid wheat landraces and wild emmer wheat accessions, some of which had previously been screened with SSR markers, for an existing SNP panel and obtained publically available genotypes for the same SNPs for hexaploid wheat varieties and landraces. Results showed that quantification of genetic diversity can be affected by ascertainment bias but that the effects of ascertainment bias can at least partly be alleviated by merging SNPs to haplotypes. Analyses of population structure and genetic differentiation show strong subdivision between the tetraploid wheat subspecies, except for durum and rivet that are not separable. A more detailed population structure of durum landraces could be obtained than with SSR markers. The results also suggest an emmer, rather than durum, ancestry of bread wheat and with gene flow from wild emmer.ConclusionsSNP markers developed for elite cultivars show great potential for inferring population structure and can address evolutionary questions in landrace wheat. Issues of marker genome specificity and mapping need, however, to be addressed. Ascertainment bias does not seem to interfere with the ability of a SNP marker system developed for elite bread wheat accessions to detect population structure in other types of wheat.
| S-EPMC4029936 | biostudies-literature
Project description:Major facilitators of water movement through plant cell membranes include aquaporin proteins. Wheat is among the largest and most important cereal crops worldwide; however, unlike other model plants such as rice, maize and Arabidopsis, little has been reported on wheat major intrinsic proteins (MIPs). This study presents a comprehensive computational identification of 349 new wheat expressed sequence tags (ESTs), encoding 13 wheat aquaporin genes. Identified aquaporins consist of 6 plasma membrane intrinsic proteins (PIP) and 1 TIP showing high sequence similarity with rice aquaporins. We also identified 4 NOD26-like intrinsic proteins (NIP) and 2 SIP members that showed more divergence. Further, expression analysis of the aquaporin genes using the available EST information in UniGene revealed their transcripts were differentially regulated in various stress- and tissue-specific libraries. Allele specific Polymerase chain reaction (PCR) primers based on single nucleotide polymorphism (SNP) were designed using PIP as the target gene and validated on a core set of Indian wheat genotypes. A 3D theoretical model of the wheat aquaporin protein was built by homology modeling and could prove to be useful in the further functional characterization of this protein. Collectively with expression and bioinformatics analysis, our results support the idea that the genes identified in this study signify an important genetic resource providing potential targets to modify the water use properties of wheat.
| S-EPMC3825567 | biostudies-literature
Project description:Wheat (Triticum aestivum L.), a globally important crop, is challenged by increasing temperatures (heat stress, HS). However its polyploid nature, the incompleteness of its genome sequences and annotation, the lack of comprehensive HS-responsive transcriptomes and the unexplored heat sensing and signaling of wheat hinder our full understanding of its adaptations to HS. The recently released genome sequences of wheat, as well as emerging single-molecular sequencing technologies, provide an opportunity to thoroughly investigate the molecular mechanisms of the wheat response to HS. We generated a high-resolution spatio-temporal transcriptome map of wheat flag leaves and filling grain under HS at 0 min, 5 min, 10 min, 30 min, 1 h and 4 h by combining full-length single-molecular sequencing and Illumina short reads sequencing. This hybrid sequencing newly discovered 4947 loci and 70 285 transcripts, generating the comprehensive and dynamic list of HS-responsive full-length transcripts and complementing the recently released wheat reference genome. Large-scale analysis revealed a global landscape of heat adaptations, uncovering unexpected rapid heat sensing and signaling, significant changes of more than half of HS-responsive genes within 30 min, heat shock factor-dependent and -independent heat signaling, and metabolic alterations in early HS-responses. Integrated analysis also demonstrated the differential responses and partitioned functions between organs and subgenomes, and suggested a differential pattern of transcriptional and alternative splicing regulation in the HS response. This study provided comprehensive data for dissecting molecular mechanisms of early HS responses in wheat and highlighted the genomic plasticity and evolutionary divergence of polyploidy wheat.
| S-EPMC6850178 | biostudies-literature
Project description:Improving salinity tolerance in the most widely cultivated cereal, bread wheat (Triticum aestivum L.), is essential to increase grain yields on saline agricultural lands. A Portuguese landrace, Mocho de Espiga Branca accumulates up to sixfold greater leaf and sheath sodium (Na+ ) than two Australian cultivars, Gladius and Scout, under salt stress in hydroponics. Despite high leaf and sheath Na+ concentrations, Mocho de Espiga Branca maintained similar salinity tolerance compared to Gladius and Scout. A naturally occurring single nucleotide substitution was identified in the gene encoding a major Na+ transporter TaHKT1;5-D in Mocho de Espiga Branca, which resulted in a L190P amino acid residue variation. This variant prevents Mocho de Espiga Branca from retrieving Na+ from the root xylem leading to a high shoot Na+ concentration. The identification of the tissue-tolerant Mocho de Espiga Branca will accelerate the development of more elite salt-tolerant bread wheat cultivars.
| S-EPMC7540593 | biostudies-literature
Project description:BACKGROUND:Wheat is a momentous crop and feeds billions of people in the world. The improvement of wheat yield is very important to ensure world food security. Normal development of grain is the essential guarantee for wheat yield formation. The genetic study of grain phenotype and identification of key genes for grain filling are of great significance upon dissecting the molecular mechanism of wheat grain morphogenesis and yield potential. RESULTS:Here we identified a pair of defective kernel (Dek) isogenic lines, BL31 and BL33, with plump and shrunken mature grains, respectively, and constructed a genetic population from the BL31/BL33 cross. Ten chromosomes had higher frequency of polymorphic single nucleotide polymorphism (SNP) markers between BL31 and BL33 using Wheat660K chip. Totally 783 simple sequence repeat (SSR) markers were chosen from the above chromosomes and 15 of these were integrated into two linkage groups using the genetic population. Genetic mapping identified three QTL, QDek.caas-3BS.1, QDek.caas-3BS.2 and QDek.caas-4AL, explaining 14.78-18.17%, 16.61-21.83% and 19.08-28.19% of phenotypic variances, respectively. Additionally, five polymorphic SNPs from Wheat660K were successfully converted into cleaved amplified polymorphic sequence (CAPS) markers and enriched the target regions of the above QTL. Biochemical analyses revealed that BL33 has significantly higher grain sucrose contents at filling stages and lower mature grain starch contents than BL31, indicating that the Dek QTL may be involved in carbohydrate metabolism. As such, the candidate genes for each QTL were predicated according to International Wheat Genome Sequence Consortium (IWGSC) RefSeq v1.0. CONCLUSIONS:Three major QTL for Dek were identified and their causal genes were predicted, laying a foundation to conduct fine mapping and dissect the regulatory mechanism underlying Dek trait in wheat.
| S-EPMC6842267 | biostudies-literature
Project description:BackgroundEight diverse sorghum (Sorghum bicolor L. Moench) accessions were subjected to short-read genome sequencing to characterize the distribution of single-nucleotide polymorphisms (SNPs). Two strategies were used for DNA library preparation. Missing SNP genotype data were imputed by local haplotype comparison. The effect of library type and genomic diversity on SNP discovery and imputation are evaluated.ResultsAlignment of eight genome equivalents (6 Gb) to the public reference genome revealed 283,000 SNPs at ≥82% confirmation probability. Sequencing from libraries constructed to limit sequencing to start at defined restriction sites led to genotyping 10-fold more SNPs in all 8 accessions, and correctly imputing 11% more missing data, than from semirandom libraries. The SNP yield advantage of the reduced-representation method was less than expected, since up to one fifth of reads started at noncanonical restriction sites and up to one third of restriction sites predicted in silico to yield unique alignments were not sampled at near-saturation. For imputation accuracy, the availability of a genomically similar accession in the germplasm panel was more important than panel size or sequencing coverage.ConclusionsA sequence quantity of 3 million 50-base reads per accession using a BsrFI library would conservatively provide satisfactory genotyping of 96,000 sorghum SNPs. For most reliable SNP-genotype imputation in shallowly sequenced genomes, germplasm panels should consist of pairs or groups of genomically similar entries. These results may help in designing strategies for economical genotyping-by-sequencing of large numbers of plant accessions.
| S-EPMC3146956 | biostudies-literature
Project description:High-throughput sequencing such as those provided by Illumina are an efficient way to understand sequence variation within viral populations. However, challenges exist in distinguishing process-introduced error from biological variance, which significantly impacts our ability to identify sub-consensus single-nucleotide variants (SNVs). Here we have taken a systematic approach to evaluate laboratory and bioinformatic pipelines to accurately identify low-frequency SNVs in viral populations. Artificial DNA and RNA "populations" were created by introducing known SNVs at predetermined frequencies into template nucleic acid before being sequenced on an Illumina MiSeq platform. These were used to assess the effects of abundance and starting input material type, technical replicates, read length and quality, short-read aligner, and percentage frequency thresholds on the ability to accurately call variants. Analyses revealed that the abundance and type of input nucleic acid had the greatest impact on the accuracy of SNV calling as measured by a micro-averaged Matthews correlation coefficient score, with DNA and high RNA inputs (107 copies) allowing for variants to be called at a 0.2% frequency. Reduced input RNA (105 copies) required more technical replicates to maintain accuracy, while low RNA inputs (103 copies) suffered from consensus-level errors. Base errors identified at specific motifs identified in all technical replicates were also identified which can be excluded to further increase SNV calling accuracy. These findings indicate that samples with low RNA inputs should be excluded for SNV calling and reinforce the importance of optimising the technical and bioinformatics steps in pipelines that are used to accurately identify sequence variants.
| S-EPMC7594041 | biostudies-literature
Project description:BackgroundThe rapid development of next generation sequencing (NGS) technology provides a novel avenue for genomic exploration and research. Single nucleotide variants (SNVs) inferred from next generation sequencing are expected to reveal gene mutations in cancer. However, NGS has lower sequence coverage and poor SNVs detection capability in the regulatory regions of the genome. Post probabilistic based methods are efficient for detection of SNVs in high coverage regions or sequencing data with high depth. However, for data with low sequencing depth, the efficiency of such algorithms remains poor and needs to be improved.ResultsA new tool SNVHMM basing on a discrete hidden Markov model (HMM) was developed to infer the genotype for each position on the genome. We incorporated the mapping quality of each read and the corresponding base quality on the reads into the emission probability of HMM. The context information of the whole observation as well as its confidence were completely utilized to infer the genotype for each position on the genome in study. Therefore, more probability power can be gained over the Bayes based methods, which is very useful for SNVs detection for data with low sequencing depth. Moreover, our model was verified by testing against two sets of lobular breast tumor and Myelodysplastic Syndromes (MDS) data each. Comparing against a recently published SNVs calling algorithm SNVMix2, our model improved the performance of SNVMix2 largely when the sequencing depth is low and also outperformed SNVMix2 when SNVMix2 is well trained by large datasets.ConclusionsSNVHMM can detect SNVs from NGS cancer data efficiently even if the sequence depth is very low. The training data size can be very small for SNVHMM to work. SNVHMM incorporated the base quality and mapping quality of all observed bases and reads, and also provides the option for users to choose the confidence of the observation for SNVs prediction.
| S-EPMC3718670 | biostudies-literature