Identification of Multiple Grain Shape-Related Loci in Rice Using Bulked Segregant Analysis With High-Throughput Sequencing.
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ABSTRACT:
SUBMITTER: Wu L
PROVIDER: S-EPMC7145986 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Oryza meyeriana is highly resistant to rice bacterial blight (BB) and this resistance trait has been transferred to cultivated rice (O. sativa) using asymmetric somatic hybridization. However, no resistance genes have yet been cloned. In the present study, a progeny of the somatic hybridization with high BB resistance was crossed with a rice cultivar with high BB susceptibility to develop an F2 population. Using bulked segregant analysis (BSA), 17 polymorphic markers that were linked to rice BB resistance were obtained through scanning a total of 186 simple sequence repeats (SSR) and sequence-tagged site (STS) markers, evenly distributed on 12 chromosomes. A genetic linkage map was then constructed based on the 17 linkage markers and the F2 segregating population, which was followed by mapping for quantitative trait loci (QTLs) for BB resistance. Three QTLs were identified on chromosomes 1, 3 and 5, respectively, and the alleles of the resistant parent at any of the QTLs increased BB resistance. All of the three QTLs had a strong effect on resistance, explaining about 21.5%, 12.3% and 39.2% of the resistance variance, respectively. These QTLs were different from the loci of the BB resistance genes that have been identified in previous studies. The QTLs mapped in this work will facilitate the isolation of novel BB resistance genes and their utilization in rice resistance breeding.
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Project description:Grain length (GL) directly affects the yield and quality of rice. Very few cloned GL-related genes are applied in production because their yield-increasing effects are not obvious, and the overall regulatory networks underlying the associated processes remain poorly understood. DNA samples from two bulk DNA pools (L-pool and S-pool) and their parents (KJ01 and Huaye 3) were subjected to high-throughput sequencing. Using bulked segregant analysis (BSA), qGL3.5 was mapped to a 0.34-Mb "hotspot" region on chromosome 3 that contains 37 genes related to various traits. Then, qGL3.5 was mapped to the genomic interval between the flanking markers M2 and M3 using 2786 BC4F2 individuals. Because the region from B5 to B6 was not the associated region under BSA-seq analysis, qGL3.5 was narrowed down to the interval between B6 and M3, which spanned 24.0-kb. Of all 37 genes with non-synonymous single-nucleotide polymorphisms (SNPs) between KJ01 and Huaye 3 based on BSA-seq analysis, only one complete annotated gene, ORF18 (Gene ID: LOC_Os03g42790.1) was found. ORF18 encodes an IBR-RING zinc-finger-related protein, with one really interesting new gene (RING) and two in between ring finger (IBR) domains. The knockout of ORF18 derived from Huaye 3 using clustered, regularly interspaced, short palindromic repeat (CRISPR)/CRISPR-associated 9 (Cas9) editing technology increased the GL of the mutant by approximately 2.2 mm. The novel locus qGL3.5 negatively regulated GL by promoting elongation of the longitudinal cell of the grain outer glume. These results provide a new genetic resource for rice grain shape breeding and a starting point for the functional characterization of the wild rice GL gene.
| S-EPMC9240483 | biostudies-literature
Project description:BACKGROUND:Cold stress can cause serious abiotic damage that limits the growth, development and yield of rice. Cold tolerance during the booting stage of rice is a key factor that can guarantee a high and stable yield under cold stress. The cold tolerance of rice is controlled by quantitative trait loci (QTLs). Based on the complex genetic basis of cold tolerance in rice, additional efforts are needed to detect reliable QTLs and identify candidate genes. In this study, recombinant inbred lines (RILs) derived from a cross between a cold sensitive variety, Dongnong422, and strongly cold-tolerant variety, Kongyu131, were used to screen for cold-tolerant loci at the booting stage of rice. RESULTS:A novel major QTL, qPSST6, controlling the percent seed set under cold water treatment (PSST) under the field conditions of 17 °C cold water irrigation was located on the 28.4 cM interval on chromosome 6. Using the combination of bulked-segregant analysis (BSA) and next-generation sequencing (NGS) technology (Seq-BSA), a 1.81 Mb region that contains 269 predicted genes on chromosome 6 was identified as the candidate region of qPSST6. Two genes, LOC_Os06g39740 and LOC_Os06g39750, were annotated as "response to cold" by gene ontology (GO) analysis. qRT-PCR analysis revealed that LOC_Os06g39750 was strongly induced by cold stress. Haplotype analysis also demonstrate a key role of LOC_Os06g39750 in regulating the PSST of rice, suggesting that it was the candidate gene of qPSST6. CONCLUSIONS:The information obtained in this study is useful for gene cloning of qPSST6 and for breeding cold-tolerant varieties of rice using marker assisted selection (MAS).
| S-EPMC5906412 | biostudies-literature
Project description:Soybean (Glycine max) has a paleopolyploid genome, and many re-sequencing experiments to characterize soybean genotypes have been conducted using next-generation sequencing platforms. The accumulation of information about single nucleotide polymorphisms (SNPs) throughout the soybean genome has accelerated identification of genomic regions related to agronomically important traits through association studies. However, although many efficient mapping techniques that use next-generation sequencing are available, the number of practical approaches to identify genes/loci is still limited. In this study, we used a combination of restriction site-associated DNA sequencing (RAD-seq) and bulk segregant analysis (BSA) to identify quantitative trait locus (QTLs) for flowering time in a segregating population derived from a cross between Japanese soybean cultivars. Despite the homogeneous genetic background of the parents, over 7000 SNPs were identified and can be used to detect QTLs by RAD-seq BSA analysis. By comparing genotype frequency between early and late-flowering bulks from the F3 segregating population, we identified a QTL on Gm10, which corresponds to the previously identified E2 locus, and a QTL on Gm04, which is close to the E8 locus. Out of these SNPs, more than 2000 were easily converted to conventional DNA markers. Our approach would improve the efficiency of genetic mapping.
| S-EPMC5515319 | biostudies-literature
Project description:Genomic regions that control traits of interest can be rapidly identified using BSA-Seq, a technology in which next-generation sequencing is applied to bulked segregant analysis (BSA). We recently developed the significant structural variant method for BSA-Seq data analysis that exhibits higher detection power than standard BSA-Seq analysis methods. Our original algorithm was developed to analyze BSA-Seq data in which genome sequences of one parent served as the reference sequences in genotype calling and, thus, required the availability of high-quality assembled parental genome sequences. Here, we modified the original script to effectively detect the genomic region-trait associations using only bulk genome sequences. We analyzed two public BSA-Seq datasets using our modified method and the standard allele frequency and G-statistic methods with and without the aid of the parental genome sequences. Our results demonstrate that the genomic region(s) associated with the trait of interest could be reliably identified via the significant structural variant method without using the parental genome sequences.
| S-EPMC9210294 | biostudies-literature
Project description:The growth habit of lateral shoots (also termed "branching habit") is an important descriptive and agronomic character of peanut. Yet, both the inheritance of branching habit and the genetic mechanism that controls it in this crop remain unclear. In addition, the low degree of polymorphism among cultivated peanut varieties hinders fine-mapping of this and other traits in non-homozygous genetic structures. Here, we combined high-throughput sequencing with a well-defined genetic system to study these issues in peanut. Initially, segregating F2 populations derived from a reciprocal cross between very closely related Virginia-type peanut cultivars with spreading and bunch growth habits were examined. The spreading/bunch trait was shown to be controlled by a single gene with no cytoplasmic effect. That gene was named Bunch1 and was significantly correlated with pod yield per plant, time to maturation and the ratio of "dead-end" pods. Subsequently, bulked segregant analysis was performed on 52 completely bunch, and 47 completely spreading F3 families. In order to facilitate the process of SNP detection and candidate-gene analysis, the transcriptome was used instead of genomic DNA. Young leaves were sampled and bulked. Reads from Illumina sequencing were aligned against the peanut reference transcriptome and the diploid genomes. Inter-varietal SNPs were detected, scored and quality-filtered. Thirty-four candidate SNPs were found to have a bulk frequency ratio value >10 and 6 of those SNPs were found to be located in the genomic region of linkage group B5. Three best hits from that over-represented region were further analyzed in the segregating population. The trait locus was found to be located in a ~1.1 Mbp segment between markers M875 (B5:145,553,897; 1.9 cM) and M255 (B5:146,649,943; 2.25 cM). The method was validated using a population of recombinant inbreed lines of the same cross and a new DNA SNP-array. This study demonstrates the relatively straight-forward utilization of bulk segregant analysis for trait fine-mapping in the low polymeric and heterozygous germplasm of cultivated peanut and provides a baseline for candidate gene discovery and map-based cloning of Bunch1.
| S-EPMC5378816 | biostudies-literature
Project description:Elite upland rice cultivars have the advantages of less water requirement along with high yield but are usually susceptible to various diseases. Rice blast caused by Magnaporthe oryzae is the most devastating disease in rice. Identification of new sources of resistance and the introgression of major resistance genes into elite cultivars are required for sustainable rice production. In this study, an upland rice genotype UR0803 was considered an emerging source of blast resistance. An F2 mapping population was developed from a cross between UR0803 and a local susceptible cultivar Lijiang Xintuan Heigu. The individuals from the F2 population were evaluated for leaf blast resistance in three trials 7 days after inoculation. Bulked segregant analysis (BSA) by high-throughput sequencing and SNP-index algorithm was performed to map the candidate region related to disease resistance trait. A major quantitative trait locus (QTL) for leaf blast resistance was identified on chromosome 11 in an interval of 1.61-Mb genomic region. The candidate region was further shortened to a 108.9-kb genomic region by genotyping the 955 individuals with 14 SNP markers. Transcriptome analysis was further performed between the resistant and susceptible parents, yielding a total of 5044 differentially expressed genes (DEGs). There were four DEGs in the candidate QTL region, of which, two (Os11g0700900 and Os11g0704000) were upregulated and the remaining (Os11g0702400 and Os11g0703600) were downregulated in the susceptible parent after inoculation. These novel candidate genes were functionally annotated to catalytic response against disease stimulus in cellular membranes. The results were further validated by a quantitative real-time PCR analysis. The fine-mapping of a novel QTL for blast resistance by integrative BSA mapping and transcriptome sequencing enhanced the genetic understanding of the mechanism of blast resistance in upland rice. The most suitable genotypes with resistance alleles would be useful genetic resources in rice blast resistance breeding.
| S-EPMC9773827 | biostudies-literature
Project description:Next-generation sequencing (NGS)-based bulked-segregant analysis (BSA) approaches have been proven successful for rapidly mapping genes in plant species. However, most such methods are based on mutants and usually only one gene controlling the mutant phenotype is identified. In this study, NGS-based BSA was employed to map simultaneously two qualitative genes controlling cotyledon color of seed in soybean. Yellow-cotyledon (YC) and green-cotyledon (GC) bulks from progenies of a biparental population (Zhonghuang 30 × Jiyu 102) were sequenced. The SNP-index of each SNP locus in YC and GC bulks was calculated and two genomic regions on chromosomes 1 and 11 harboring, respectively, loci qCC1 and qCC2 were identified by ?(SNP-index) analysis. These two BSA-seq-derived loci were further validated with SSR markers and fine-mapped. qCC1 was mapped to a 30.7-kb region containing four annotated genes and qCC2 was mapped to a 67.7-kb region with nine genes. These two regions contained, respectively, genes D1 and D2, which had previously been identified by homology-based cloning as being associated with cotyledon color. Sequence analysis of the NGS data also identified a frameshift deletion in the coding region of D1. These results suggested that BSA-seq could accelerate the mapping of loci controlling qualitative traits, even if a trait is controlled by more than one locus.
| S-EPMC5449466 | biostudies-literature
Project description:Yellow seed breeding is an effective method to improve oil yield and quality in rapeseed (Brassica napus L.). However, naturally occurring yellow-seeded genotypes have not been identified in B. napus. Mustard (Brassica juncea L.) has some natural, yellow-seeded germplasms, yet the molecular mechanism underlying this trait remains unclear. In this study, a BC9 population derived from the cross of yellow seed mustard "Wuqi" and brown seed mustard "Wugong" was used to analyze the candidate genes controlling the yellow seed color of B. juncea. Subsequently, yellow-seeded (BY) and brown-seeded (BB) bulks were constructed in the BC9 population and subjected to bulked segregant RNA sequencing (BSR-Seq). A total of 511 differentially expressed genes (DEGs) were identified between the brown and yellow seed bulks. Enrichment analysis revealed that these DEGs were involved in the phenylpropanoid biosynthetic process and flavonoid biosynthetic process, including key genes such as 4CL, C4H, LDOX/TT18, PAL1, PAL2, PAL4, TT10, TT12, TT4, TT8, BAN, DFR/TT3, F3H/TT6, TT19, and CHI/TT5. In addition, 111,540 credible single-nucleotide polymorphisms (SNPs) and 86,319 INDELs were obtained and used for quantitative trait locus (QTL) identification. Subsequently, two significant QTLs on chromosome A09, namely, qSCA09-3 and qSCA09-7, were identified by G' analysis, and five DEGs (BjuA09PAL2, BjuA09TT5, BjuA09TT6, BjuA09TT4, BjuA09TT3) involved in the flavonoid pathway were identified as hub genes based on the protein-to-protein network. Among these five genes, only BjuA09PAL2 and BjuA09F3H had SNPs between BY and BB bulks. Interestingly, the majority of SNPs in BjuA09PAL2 were consistent with the SNPs identified between the high-quality assembled B. juncea reference genome "T84-66" (brown-seed) and "AU213" (yellow-seed). Therefore, BjuA09PAL2, which encodes phenylalanine lyase, was considered as the candidate gene associated with yellow seed color of B. juncea. The identification of a novel gene associated with the yellow seed coloration of B. juncea through this study may play a significant role in enhancing yellow seed breeding in rapeseed.
| S-EPMC10855766 | biostudies-literature
Project description:BackgroundCommon buckwheat (2n = 2x = 16) is an outcrossing pseudocereal whose seeds contain abundant nutrients and potential antioxidants. As these beneficial compounds are damaged by preharvest sprouting (PHS) and PHS is likely to increase with global warming, it is important to find efficient ways to develop new PHS-tolerant lines. However, genetic loci and selection markers associated with PHS in buckwheat have not been reported.ResultsBy next-generation sequencing (NGS) of whole-genome of parental lines, we developed a genome-wide set of 300 markers. By NGS- based bulked segregant analysis (NGS-BSA), we developed 100 markers linked to PHS tolerance. To confirm the effectiveness of marker development from NGS-BSA data, we developed 100 markers linked to the self-compatibility (SC) trait from previous NGS-BSA data. Using these markers, we developed genetic maps with AmpliSeq technology, which can quickly detect polymorphisms by amplicon-based multiplex targeted NGS, and performed quantitative trait locus (QTL) analysis for PHS tolerance in combination with NGS-BSA. QTL analysis detected two major and two minor QTLs for PHS tolerance in a segregating population developed from a cross between the PHS-tolerant 'Kyukei 29' and the self-compatible susceptible 'Kyukei SC7'. We found different major and minor QTLs in other segregating populations developed from the PHS-tolerant lines 'Kyukei 28' and 'NARO-FE-1'. Candidate markers linked to PHS developed by NGS-BSA were located near these QTL regions. We also investigated the effectiveness of markers linked to these QTLs for selection of PHS-tolerant lines among other segregating populations.ConclusionsWe efficiently developed genetic maps using a method combined with AmpliSeq technology and NGS-BSA, and detected QTLs associated with preharvest sprouting tolerance in common buckwheat. This is the first report to identify QTLs for PHS tolerance in buckwheat. Our marker development system will accelerate genetic research and breeding in common buckwheat.
| S-EPMC7789488 | biostudies-literature