Rapid identification of major QTLs associated with rice grain weight and their utilization

Impairment in a member of AP2/ERF and F-box family protein enhances complete panicle exsertion in rice

Complete panicle exsertion (CPE) is an economically important quantitative trait that contributes to grain yield in rice. We deployed an integrated approach for understanding the molecular mechanism of CPE using a stable ethyl methanesulfonate mutant line, CPE-109 of the Samba Mahsuri (SM) variety of rice (Oryza sativa), which exhibits CPE. Two consistent genomic regions were identified for CPE through quantitative trait locus (QTL) mapping [qCPE-4 (28.24-31.22 Mb) and qCPE-12 (2.30-3.18 Mb)] and QTL-sequencing [chr 4 (31.21-33.69 Mb) and chr 12 (0.12-3.15 Mb)]. Two non-synonymous single nucleotide polymorphisms, namely KASP 12-12 (T→C; chr12:1269983) in Os12g0126300, encoding an AP2/ERF transcription factor, and KASP 12-16 (G→A; chr12:1515198) in Os12g0131400, encoding an F-box domain-containing protein, explained 81.05% and 59.61% of the phenotypic variance, respectively, and exhibited strong co-segregation with CPE in F2 mapping populations, advanced generation lines, and CPE-exhibiting SM mutants through KASP assays. Down-regulation of these genes in CPE-109 compared with SM (wild type) was observed in transcriptome sequencing of flag leaves, which was validated through qRT-PCR. We propose that the abrogation of Os12g0126300 and Os12g0131400 in CPE-109 combinatorially influences down-regulation of ethylene biosynthetic genes, Os01g0192900 (ACC synthase) and Os05g0497300 (ethylene-responsive factor-2), and up-regulation of a gibberellic acid synthetic gene, Os06g0569900 (ent-kaurene synthase) and the two cytokinin biosynthetic genes Os07g0486700 (cytokinin-O-glucosyltransferase 2) and Os10g0479500 (similar to carboxy-lyase), which results in complete panicle exsertion.

Evaluation of deep learning for predicting rice traits using structural and single-nucleotide genomic variants

BACKGROUND

Structural genomic variants (SVs) are prevalent in plant genomes and have played an important role in evolution and domestication, as they constitute a significant source of genomic and phenotypic variability. Nevertheless, most methods in quantitative genetics focusing on crop improvement, such as genomic prediction, consider only Single Nucleotide Polymorphisms (SNPs). Deep Learning (DL) is a promising strategy for genomic prediction, but its performance using SVs and SNPs as genetic markers remains unknown.

RESULTS

We used rice to investigate whether combining SVs and SNPs can result in better trait prediction over SNPs alone and examine the potential advantage of Deep Learning (DL) networks over Bayesian Linear models. Specifically, the performances of BayesC (considering additive effects) and a Bayesian Reproducible Kernel Hilbert space (RKHS) regression (considering both additive and non-additive effects) were compared to those of two different DL architectures, the Multilayer Perceptron, and the Convolution Neural Network, to explore their prediction ability by using various marker input strategies. We found that exploiting structural and nucleotide variation slightly improved prediction ability on complex traits in 87% of the cases. DL models outperformed Bayesian models in 75% of the studied cases, considering the four traits and the two validation strategies used. Finally, DL systematically improved prediction ability of binary traits against the Bayesian models.

CONCLUSIONS

Our study reveals that the use of structural genomic variants can improve trait prediction in rice, independently of the methodology used. Also, our results suggest that Deep Learning (DL) networks can perform better than Bayesian models in the prediction of binary traits, and in quantitative traits when the training and target sets are not closely related. This highlights the potential of DL to enhance crop improvement in specific scenarios and the importance to consider SVs in addition to SNPs in genomic selection.

Agronomic potential of plant-specific Gγ proteins

The vascular plant-specific type III Gγ proteins have emerged as important targets for biotechnological applications. These proteins are exemplified by Arabidopsis AGG3, rice Grain Size 3 (GS3), Dense and Erect Panicle 1 (DEP1), and GGC2 and regulate plant stature, seed size, weight and quality, nitrogen use efficiency, and multiple stress responses. These Gγ proteins are an integral component of the plant heterotrimeric G-protein complex and differ from the canonical Gγ proteins due to the presence of a long, cysteine-rich C-terminal region. Most cereal genomes encode three or more of these proteins, which have similar N-terminal Gγ domains but varying lengths of the C-terminal domain. The C-terminal domain is hypothesized to give specificity to the protein function. Intriguingly, many accessions of cultivated cereals have natural deletion of this region in one or more proteins, but the mechanistic details of protein function remain perplexing. Distinct, sometimes contrasting, effects of deletion of the C-terminal region have been reported in different crops or under varying environmental conditions. This review summarizes the known roles of type III Gγ proteins, the possible action mechanisms, and a perspective on what is needed to comprehend their full agronomic potential.

BSR and Full-Length Transcriptome Approaches Identified Candidate Genes for High Seed Ratio in Camellia vietnamensis

(1) Background: C. vietnamensis is very suitable for growth in the low hilly areas of southern subtropical regions. Under appropriate conditions, the oil yield of C. vietnamensis can reach 1125 kg/ha (the existing varieties can reach 750 kg/ha). Moreover, the fruit of C. vietnamensis is large and the pericarp is thick (>5 cm). Therefore, a high seed ratio has become the main target economic trait for the breeding of C. vietnamensis. (2) Methods: A half-sibling population of C. vietnamensis plants with a combination of high and low seed ratios was constructed by crossing a C. vietnamensis female parent. Bulked segregant RNA analysis and full-length transcriptome sequencing were performed to determine the molecular mechanisms underlying a high seed ratio. (3) Results: Seed ratio is a complex quantitative trait with a normal distribution, which is significantly associated with four other traits of fruit (seed weight, seed number, fruit diameter, and pericarp thickness). Two candidate regions related to high seed ratio (HSR) were predicted. One spanned 140.8−148.4 Mb of chromosome 2 and was associated with 97 seed-yield-related candidate genes ranging in length from 278 to 16,628 bp. The other spanned 35.3−37.3 Mb on chromosome 15 and was associated with 38 genes ranging in length from 221 to 16,928 bp. Using the full-length transcript as a template, a total of 115 candidate transcripts were obtained, and 78 transcripts were predicted to be functionally annotated. The DEGs from two set pairs of cDNA sequencing bulks were enriched to cytochrome p450 CYP76F14 (KOG0156; GO:0055114, HSR4, HSR7), the gibberellin phytohormone pathway (GO:0016787, HSR5), the calcium signaling pathway (GO:0005509, HSR6), the polyubiquitin-PPAR signaling pathway (GO:0005515, HSR2, HSR3), and several main transcription factors (bZIP transcription factor, HSR1) in C. vietnamensis.

Detection of QTLs Regulating Six Agronomic Traits of Rice Based on Chromosome Segment Substitution Lines of Common Wild Rice (Oryza rufipogon Griff.) and Mapping of qPH1.1 and qLMC6.1

Wild rice is a primary source of genes that can be utilized to generate rice cultivars with advantageous traits. Chromosome segment substitution lines (CSSLs) are consisting of a set of consecutive and overlapping donor chromosome segments in a recipient's genetic background. CSSLs are an ideal genetic population for mapping quantitative traits loci (QTLs). In this study, 59 CSSLs from the common wild rice (Oryza rufipogon Griff.) accession DP15 under the indica rice cultivar (O. sativa L. ssp. indica) variety 93-11 background were constructed through multiple backcrosses and marker-assisted selection (MAS). Through high-throughput whole genome re-sequencing (WGRS) of parental lines, 12,565 mapped InDels were identified and designed for polymorphic molecular markers. The 59 CSSLs library covered 91.72% of the genome of common wild rice accession DP15. The DP15-CSSLs displayed variation in six economic traits including grain length (GL), grain width (GW), thousand-grain weight (TGW), grain length-width ratio (GLWR), plant height (PH), and leaf margin color (LMC), which were finally attributed to 22 QTLs. A homozygous CSSL line and a purple leave margin CSSL line were selected to construct two secondary genetic populations for the QTLs mapping. Thus, the PH-controlling QTL qPH1.1 was mapped to a region of 4.31-Mb on chromosome 1, and the LMC-controlling QTL qLMC6.1 was mapped to a region of 370-kb on chromosome 6. Taken together, these identified novel QTLs/genes from common wild rice can potentially promote theoretical knowledge and genetic applications to rice breeders worldwide.

A meta-quantitative trait loci analysis identified consensus genomic regions and candidate genes associated with grain yield in rice

Improving grain yield potential in rice is an important step toward addressing global food security challenges. The meta-QTL analysis offers stable and robust QTLs irrespective of the genetic background of mapping populations and phenotype environment and effectively narrows confidence intervals (CI) for candidate gene (CG) mining and marker-assisted selection improvement. To achieve these aims, a comprehensive bibliographic search for grain yield traits (spikelet fertility, number of grains per panicle, panicles number per plant, and 1000-grain weight) QTLs was conducted, and 462 QTLs were retrieved from 47 independent QTL research published between 2002 and 2022. QTL projection was performed using a reference map with a cumulative length of 2,945.67 cM, and MQTL analysis was conducted on 313 QTLs. Consequently, a total of 62 MQTLs were identified with reduced mean CI (up to 3.40 fold) compared to the mean CI of original QTLs. However, 10 of these MQTLs harbored at least six of the initial QTLs from diverse genetic backgrounds and environments and were considered the most stable and robust MQTLs. Also, MQTLs were compared with GWAS studies and resulted in the identification of 16 common significant loci modulating the evaluated traits. Gene annotation, gene ontology (GO) enrichment, and RNA-seq analyses of chromosome regions of the stable MQTLs detected 52 potential CGs including those that have been cloned in previous studies. These genes encode proteins known to be involved in regulating grain yield including cytochrome P450, zinc fingers, MADs-box, AP2/ERF domain, F-box, ubiquitin ligase domain protein, homeobox domain, DEAD-box ATP domain, and U-box domain. This study provides the framework for molecular dissection of grain yield in rice. Moreover, the MQTLs and CGs identified could be useful for fine mapping, gene cloning, and marker-assisted selection to improve rice productivity.

Transposable element polymorphisms improve prediction of complex agronomic traits in rice

KEY MESSAGE

Transposon insertion polymorphisms can improve prediction of complex agronomic traits in rice compared to using SNPs only, especially when accessions to be predicted are less related to the training set. Transposon insertion polymorphisms (TIPs) are significant sources of genetic variation. Previous work has shown that TIPs can improve detection of causative loci on agronomic traits in rice. Here, we quantify the fraction of variance explained by single nucleotide polymorphisms (SNPs) compared to TIPs, and we explore whether TIPs can improve prediction of traits when compared to using only SNPs. We used eleven traits of agronomic relevance from by five different rice population groups (Aus, Indica, Aromatic, Japonica, and Admixed), 738 accessions in total. We assess prediction by applying data split validation in two scenarios. In the within-population scenario, we predicted performance of improved Indica varieties using the rest of Indica accessions. In the across population scenario, we predicted all Aromatic and Admixed accessions using the rest of populations. In each scenario, Bayes C and a Bayesian reproducible kernel Hilbert space regression were compared. We find that TIPs can explain an important fraction of total genetic variance and that they also improve genomic prediction. In the across population prediction scenario, TIPs outperformed SNPs in nine out of the eleven traits analyzed. In some traits like leaf senescence or grain width, using TIPs increased predictive correlation by 30-50%. Our results evidence, for the first time, that TIPs genotyping can improve prediction on complex agronomic traits in rice, especially when accessions to be predicted are less related to training accessions.

Understanding complex genetic architecture of rice grain weight through QTL-meta analysis and candidate gene identification

Quantitative trait loci (QTL) for rice grain weight identified using bi-parental populations in various environments were found inconsistent and have a modest role in marker assisted breeding and map-based cloning programs. Thus, the identification of a consistent consensus QTL region across populations is critical to deploy in marker aided breeding programs. Using the QTL meta-analysis technique, we collated rice grain weight QTL information from numerous studies done across populations and in diverse environments to find constitutive QTL for grain weight. Using information from 114 original QTL in meta-analysis, we discovered three significant Meta-QTL (MQTL) for grain weight on chromosome 3. According to gene ontology, these three MQTL have 179 genes, 25 of which have roles in developmental functions. Amino acid sequence BLAST of these genes indicated their orthologue conservation among core cereals with similar functions. MQTL3.1 includes the OsAPX1, PDIL, SAUR, and OsASN1 genes, which are involved in grain development and have been discovered to play a key role in asparagine biosynthesis and metabolism, which is crucial for source-sink regulation. Five potential candidate genes were identified and their expression analysis indicated a significant role in early grain development. The gene sequence information retrieved from the 3 K rice genome project revealed the deletion of six bases coding for serine and alanine in the last exon of OsASN1 led to an interruption in the synthesis of α-helix of the protein, which negatively affected the asparagine biosynthesis pathway in the low grain weight genotypes. Further, the MQTL3.1 was validated using linked marker RM7197 on a set of genotypes with extreme phenotypes. MQTL that have been identified and validated in our study have significant scope in MAS breeding and map-based cloning programs for improving rice grain weight.

Identification of Genetic Loci for Sugarcane Leaf Angle at Different Developmental Stages by Genome-Wide Association Study

Sugarcane (Saccharum spp.) is an efficient crop mainly used for sugar and bioethanol production. High yield and high sucrose of sugarcane are always the fundamental demands in sugarcane growth worldwide. Leaf angle and size of sugarcane can be attributed to planting density, which was associated with yield. In this study, we performed genome-wide association studies (GWAS) with a panel of 216 sugarcane core parents and their derived lines (natural population) to determine the genetic basis of leaf angle and key candidate genes with +2, +3, and +4 leaf at the seedling, elongation, and mature stages. A total of 288 significantly associated loci of sugarcane leaf angle at different developmental stages (eight phenotypes) were identified by GWAS with 4,027,298 high-quality SNP markers. Among them, one key locus and 11 loci were identified in all three stages and two stages, respectively. An InDel marker (SNP Ss6A_102766953) linked to narrow leaf angle was obtained. Overall, 4,089 genes were located in the confidence interval of significant loci, among which 3,892 genes were functionally annotated. Finally, 13 core parents and their derivatives tagged with SNPs were selected for marker-assisted selection (MAS). These candidate genes are mainly related to MYB transcription factors, auxin response factors, serine/threonine protein kinases, etc. They are directly or indirectly associated with leaf angle in sugarcane. This research provided a large number of novel genetic resources for the improvement of leaf angles and simultaneously to high yield and high bioethanol production.

Identifying Quantitative Trait Loci for Thousand Grain Weight in Eggplant by Genome Re-Sequencing Analysis

Eggplant (Solanum melongena L.; 2n = 24) is one of the most important Solanaceae vegetables and is primarily cultivated in China (approximately 42% of world production) and India (approximately 39%). Thousand-grain weight (TGW) is an important trait that affects eggplant breeding cost and variety promotion. This trait is controlled by quantitative trait loci (QTLs); however, no quantitative trait loci (QTL) has been reported for TGW in eggplant so far, and its potential genetic basis remain unclear. In this study, two eggplant lines, 17C01 (P1, wild resource, small seed) and 17C02 (P2, cultivar, large seed), were crossed to develop F1, F2 (308 lines), BC1P1 (44 lines), and BC1P2 (44 lines) populations for quantitative trait association analysis. The TGWs of P1, P2 and F1 were determined as 3.00, 3.98 and 3.77 g, respectively. The PG-ADI (polygene-controlled additive-dominance-epistasis) genetic model was identified as the optimal model for TGW and the polygene heritability value in the F2 generation was as high as 80.87%. A high-quality genetic linkage bin map was constructed with resequencing analysis. The map contained 3,918 recombination bins on 12 chromosomes, and the total length was 1,384.62 cM. A major QTL (named as TGW9.1) located on chromosome 9 was identified to be strongly associated with eggplant TGW, with a phenotypic variance explanation of 20.51%. A total of 45 annotated genes were identified in the genetic region of TGW9.1. Based on the annotation of Eggplant genome V3 and orthologous genes in Arabidopsis thaliana, one candidate gene SMEL_009g329850 (SmGTS1, encoding a putative ubiquitin ligase) contains 4 SNPs and 2 Indels consecutive intron mutations in the flank of the same exon in P1. SmGTS1 displayed significantly higher expression in P1 and was selected as a potential candidate gene controlling TGW in eggplant. The present results contribute to shed light on the genetic basis of the traits exploitable in future eggplant marker-assisted selection (MAS) breeding.

Identification of starch candidate genes using SLAF-seq and BSA strategies and development of related SNP-CAPS markers in tetraploid potato

Potato starch is an essential nutrient for humans and is widely used worldwide. Locating relevant genomic regions, mining stable genes and developing candidate gene markers can promote the breeding of new high-starch potato varieties. A total of 106 F₁ individuals and their parents (YSP-4 × MIN-021) were used as test materials, from which 20 plants with high starch content and 20 with low starch content were selected to construct DNA pools for site-specific amplified fragment sequencing (SLAF-seq) and bulked segregation analysis (BSA). A genomic region related to the starch traits was first identified in the 0–5.62 Mb of chromosome 2 in tetraploid potato. In this section, a total of 41 non-synonymous genes, which were considered as candidate genes related to the starch trait, were annotated through a basic local alignment search tool (BLAST) search of multiple databases. Six candidate genes for starch (PGSC0003DMG400017793, PGSC0003DMG400035245, PGSC0003DMG400036713, PGSC0003DMG400040452, PGSC0003DMG400006636 and PGSC0003DMG400044547) were further explored. In addition, cleaved amplified polymorphic sequence (CAPS) markers were developed based on single nucleotide polymorphism (SNP) sites associated with the starch candidate genes. SNP-CAPS markers chr2-CAPS6 and chr2-CAPS21 were successfully developed and validated with the F₂ population and 24 tetraploid potato varieties (lines). Functional analysis and cloning of the candidate genes associated with potato starch will be performed in further research, and the SNP-CAPS markers chr2-CAPS6 and chr2-CAPS21 can be further used in marker-assisted selection breeding of tetraploid potato varieties with high starch content.

Understanding Omics Driven Plant Improvement and de novo Crop Domestication: Some Examples

In the current era, one of biggest challenges is to shorten the breeding cycle for rapid generation of a new crop variety having high yield capacity, disease resistance, high nutrient content, etc. Advances in the "-omics" technology have revolutionized the discovery of genes and bio-molecules with remarkable precision, resulting in significant development of plant-focused metabolic databases and resources. Metabolomics has been widely used in several model plants and crop species to examine metabolic drift and changes in metabolic composition during various developmental stages and in response to stimuli. Over the last few decades, these efforts have resulted in a significantly improved understanding of the metabolic pathways of plants through identification of several unknown intermediates. This has assisted in developing several new metabolically engineered important crops with desirable agronomic traits, and has facilitated the de novo domestication of new crops for sustainable agriculture and food security. In this review, we discuss how "omics" technologies, particularly metabolomics, has enhanced our understanding of important traits and allowed speedy domestication of novel crop plants.

Sequence Variants Linked to Key Traits in Interspecific Crosses between African and Asian Rice

Asian and African rice gene pools vary in many traits that are important in rice breeding. The genetic basis of these differences was evaluated by analysis of important agronomic traits in crosses between African and Asian rice. Trait-associated variants (TAVs) influencing three quantitative agronomic traits, heading date (Hd), tiller number at maturity (T), and 1000 grain weight (TGW), were identified by association analysis of crosses between Asian and African rice. Populations were developed by crossing WAB56-104 (Oryza sativa) and CG14 (Oryza glaberrima). DNA from plants with extremely high or low values for these phenotypes was bulked and sequenced. The reference genome of O. sativa cv Nipponbare was used in general association analysis and candidate gene analysis. A total of 5152 non-synonymous single nucleotide polymorphisms (SNPs) across 3564 genes distinguished the low and the high bulks for Hd, T, and TGW traits; 611 non-synonymous SNPs across 447 genes were found in KEGG pathways. Six non-synonymous SNPs were found in the sequences of LOC107275952, LOC4334529, LOC4326177, LOC107275432, LOC4335790, and LOC107275425 genes associated with Hd, T, and TGW traits. These genes were involved in: abscisic-acid biosynthesis, carotenoid biosynthesis, starch and sucrose metabolism, and cytokinin biosynthesis. Analysis of 24 candidate genes associated with Hd, T, and TGW traits showed seven non-synonymous variations in the sequence of Hd3a and Ehd2 from the Hd genes (not in a KEGG pathway), D10 and D53 from the T genes (strigolactones biosynthetic pathway), and Gn1a and GIF1 from the TGW genes (cytokinin biosynthetic and starch and sucrose metabolism pathways). This study identified significant differences in allele frequencies supported by high sequence depth in analysis of bulks displaying high and low values for these key traits. These trait-associated variants are likely to be useful in rice improvement.

Genome-Wide Association Study of Grain Size Traits in Indica Rice Multiparent Advanced Generation Intercross (MAGIC) Population

Rice grain size plays a crucial role in determining grain quality and yield. In this study, two multiparent advanced generation intercross (MAGIC) populations, DC1 and BIM, were evaluated for grain size across three environments and genotyped with 55K array-based SNP detection and genotype-by-sequencing (GBS), respectively, to identify QTLs and SNPs associated with grain length, grain width, grain length-width ratio, grain thickness, and thousand grain weight. A total of 18 QTLs were identified for the five grain size-related traits and explained 6.43-63.35% of the total phenotypic variance. Twelve of these QTLs colocalized with the cloned genes, GS3, GW5/qSW5, GW7/GL7/SLG7, and GW8/OsSPL16, of which the first two genes showed the strongest effect for grain length and grain width, respectively. Four potential new genes were also identified from the QTLs, which exhibited both genetic background independency and environment stability and could be validated in future studies. Moreover, the significant SNP markers identified are valuable for direct utilization in marker-assisted breeding to improve rice grain size.

Genome wide screening and comparative genome analysis for Meta-QTLs, ortho-MQTLs and candidate genes controlling yield and yield-related traits in rice

Background

Improving yield and yield-related traits is the crucial goal in breeding programmes of cereals. Meta-QTL (MQTL) analysis discovers the most stable QTLs regardless of populations genetic background and field trial conditions and effectively narrows down the confidence interval (CI) for identification of candidate genes (CG) and markers development.

Results

A comprehensive MQTL analysis was implemented on 1052 QTLs reported for yield (YLD), grain weight (GW), heading date (HD), plant height (PH) and tiller number (TN) in 122 rice populations evaluated under normal condition from 1996 to 2019. Consequently, these QTLs were confined into 114 MQTLs and the average CI was reduced up to 3.5 folds in compare to the mean CI of the original QTLs with an average of 4.85 cM CI in the resulted MQTLs. Among them, 27 MQTLs with at least five initial QTLs from independent studies were considered as the most stable QTLs over different field trials and genetic backgrounds. Furthermore, several known and novel CGs were detected in the high confident MQTLs intervals. The genomic distribution of MQTLs indicated the highest density at subtelomeric chromosomal regions. Using the advantage of synteny and comparative genomics analysis, 11 and 15 ortho-MQTLs were identified at co-linear regions between rice with barley and maize, respectively. In addition, comparing resulted MQTLs with GWAS studies led to identification of eighteen common significant chromosomal regions controlling the evaluated traits.

Conclusion

This comprehensive analysis defines a genome wide landscape on the most stable loci associated with reliable genetic markers and CGs for yield and yield-related traits in rice. Our findings showed that some of these information are transferable to other cereals that lead to improvement of their breeding programs.

Identification of QTL TGW12 responsible for grain weight in rice based on recombinant inbred line population crossed by wild rice (Oryza minuta) introgression line K1561 and indica rice G1025

Background

Limited genetic resource in the cultivated rice may hinder further yield improvement. Some valuable genes that contribute to rice yield may be lost or lacked in the cultivated rice. Identification of the quantitative trait locus (QTL) for yield-related traits such as thousand-grain weight (TGW) from wild rice speices is desired for rice yield improvement.

Results

In this study, sixteen TGW QTL were identified from a recombinant inbred line (RIL) population derived from the cross between the introgression line K1561 of Oryza minuta and the rice cultivar G1025. TGW12, One of most effective QTL was mapped to the region of 204.12 kb between the marker 2,768,345 and marker 2,853,491 of the specific locus amplified fragment (SLAF). The origin of TGW12 was tested using three markers nearby or within the TGW12 region, but not clarified yet. Our data indicated thirty-two open reading fragments (ORFs) were present in the region. RT-PCR analysis and sequence alignment showed that the coding domain sequences of ORF12, one MADS-box gene, in G1025 and K1561 were different due to alternative slicing, which caused premature transcription termination. The MADS-box gene was considered as a candidate of TGW12.

Conclusion

The effective QTL, TGW12, was mapped to a segment of 204.12 kb using RILs population and a MADS-box gene was identified among several candidate genes in the segment. The region of TGW12 should be further narrowed and creation of transgenic lines will reveal the gene function. TGW12 could be applied for improvement of TGW in breeding program.

Identification of a Major QTL (qRRs-10.1) That Confers Resistance to Ralstonia solanacearum in Pepper (Capsicum annuum) Using SLAF-BSA and QTL Mapping

The soilborne pathogen Ralstonia solanacearum is the causal agent of bacterial wilt (BW), a major disease of pepper (Capsicum annuum). The genetic basis of resistance to this disease in pepper is not well known. This study aimed to identify BW resistance markers in pepper. Analysis of the dynamics of bioluminescent R. solanacearum colonization in reciprocal grafts of a resistant (BVRC 1) line and a susceptible (BVRC 25) line revealed that the resistant rootstock effectively suppressed the spreading of bacteria into the scion. The two clear-cut phenotypic distributions of the disease severity index in 440 F2 plants derived from BVRC 25 × BVRC 1 indicated that a major genetic factor as well as a few minor factors that control BW resistance. By specific-locus amplified fragment sequencing combined with bulked segregant analysis, two adjacent resistance-associated regions on chromosome 10 were identified. Quantitative trait (QTL) mapping revealed that these two regions belong to a single QTL, qRRs-10.1. The marker ID10-194305124, which reached a maximum log-likelihood value at 9.79 and accounted for 19.01% of the phenotypic variation, was located the closest to the QTL peak. A cluster of five predicted R genes and three defense-related genes, which are located in close proximity to the significant markers ID10-194305124 or ID10-196208712, are important candidate genes that may confer BW resistance in pepper.

Construction of the first high-density genetic linkage map and identification of seed yield-related QTLs and candidate genes in Elymus sibiricus, an important forage grass in Qinghai-Tibet Plateau

Background

Elymus sibiricus is an ecologically and economically important perennial, self-pollinated, and allotetraploid (StStHH) grass, widely used for forage production and animal husbandry in Western and Northern China. However, it has low seed yield mainly caused by seed shattering, which makes seed production difficult for this species. The goals of this study were to construct the high-density genetic linkage map, and to identify QTLs and candidate genes for seed-yield related traits.

Results

An F₂ mapping population of 200 individuals was developed from a cross between single genotype from “Y1005” and “ZhN06”. Specific-locus amplified fragment sequencing (SLAF-seq) was applied to construct the first genetic linkage map. The final genetic map included 1971 markers on the 14 linkage groups (LGs) and was 1866.35 cM in total. The length of each linkage group varied from 87.67 cM (LG7) to 183.45 cM (LG1), with an average distance of 1.66 cM between adjacent markers. The marker sequences of E. sibiricus were compared to two grass genomes and showed 1556 (79%) markers mapped to wheat, 1380 (70%) to barley. Phenotypic data of eight seed-related traits (2016–2018) were used for QTL identification. A total of 29 QTLs were detected for eight seed-related traits on 14 linkage groups, of which 16 QTLs could be consistently detected for two or three years. A total of 6 QTLs were associated with seed shattering. Based on annotation with wheat and barley genome and transcriptome data of abscission zone in E. sibiricus, we identified 30 candidate genes for seed shattering, of which 15, 7, 6 and 2 genes were involved in plant hormone signal transcription, transcription factor, hydrolase activity and lignin biosynthetic pathway, respectively.

Conclusion

This study constructed the first high-density genetic linkage map and identified QTLs and candidate genes for seed-related traits in E. sibiricus. Results of this study will not only serve as genome-wide resources for gene/QTL fine mapping, but also provide a genetic framework for anchoring sequence scaffolds on chromosomes in future genome sequence assembly of E. sibiricus.

QTL-BSA: A Bulked Segregant Analysis and Visualization Pipeline for QTL-seq

In recent years, the application of Whole Genome Sequencing (WGS) on plants has generated sufficient data for the identification of trait-associated genomic loci or genes. A high-throughput genome-assisted QTL-seq strategy, combined with bulked-segregant analysis and WGS of two bulked populations from a segregating progeny with opposite phenotypic trait values, has gained increasing popularities in research community. However, there is no publicly available user friendly software for the identification and visualization. Hence, we developed a tool named QTL-BSA (QTL-bulked segregant analysis and visualization pipeline), which could facilitate the rapid identification and visualization of candidate QTLs from QTL-seq. As a proof-of-concept study, we have applied the tool for the rapid discovery and the identification of genes related with the partial blast resistance in rice. Genomic region of the major QTL identified on chromosome 6, is located between 1.52 and 4.32 Mb, which is consistent with previous studies (2.39-4.39 Mb). We also derived the gene and QTLs functional annotation of this region. QTL-BSA offers a comprehensive solution to facilitate a wide range of programming and visualization tasks in QTL-seq analysis, is expected to be used widely by the research community.

QTL mapping pod dehiscence resistance in soybean (Glycine max L. Merr.) using specific-locus amplified fragment sequencing

KEY MESSAGE

We constructed a high-density genetic linkage map comprising 4,593 SLAF markers using specific-locus amplified fragment sequencing and identified six quantitative trait loci for pod dehiscence resistance in soybean. Pod dehiscence is necessary for propagation in wild soybean (Glycine soja). It is a major component causing yield losses in cultivated soybean, however, and thus, cultivated soybean varieties have been artificially selected for resistance to pod dehiscence. Detecting quantitative trait loci (QTLs) related to pod dehiscence is required for molecular marker-assisted selection for breeding new varieties with pod dehiscence resistance. In this study, we constructed a high-density genetic linkage map using 260 recombinant inbred lines derived from the cultivars of Heihe 43 (pod-indehiscent) (ZDD24325) and Heihe 18 (pod-dehiscent) (ZDD23620). The map contained 4953 SLAF markers spanning 1478.86 cM on 20 linkage groups with an average distance between adjacent markers of 0.53 cM. In total, six novel QTLs related to pod dehiscence were mapped using inclusive composite interval mapping, explaining 7.22-24.44% of the phenotypic variance across 3 years, including three stable QTLs (qPD01, qPD05-1 and qPD08-1), that had been validated by developing CAPS/dCAPS markers. Based on the SNP/Indel and significant differential expression analyses of two parents, seven genes were selected as candidate genes for future study. The high-density map, three stable QTLs and their molecular markers will be helpful for map-based cloning of pod dehiscence resistance genes and marker-assisted selection of pod dehiscence resistance in soybean breeding.

Molecular insights into the regulation of rice kernel elongation

A large number of rice agronomic traits are complex, multi factorial and polygenic. As the mechanisms and genes determining grain size and yield are largely unknown, the identification of regulatory genes related to grain development remains a preeminent approach in rice genetic studies and breeding programs. Genes regulating cell proliferation and expansion in spikelet hulls and participating in endosperm development are the main controllers of rice kernel elongation and grain size. We review here and discuss recent findings on genes controlling rice grain size and the mechanisms, epialleles, epigenomic variation, and assessment of controlling genes using genome-editing tools relating to kernel elongation.

Identification of genomic regions associated with multi-silique trait in Brassica napus

BACKGROUND

Although rapeseed (Brassica napus L.) mutant forming multiple siliques was morphologically described and considered to increase the silique number per plant, an important agronomic trait in this crop, the molecular mechanism underlying this beneficial trait remains unclear. Here, we combined bulked-segregant analysis (BSA) and whole genome re-sequencing (WGR) to map the genomic regions responsible for the multi-silique trait using two pools of DNA from the near-isogenic lines (NILs) zws-ms (multi-silique) and zws-217 (single-silique). We used the Euclidean Distance (ED) to identify genomic regions associated with this trait based on both SNPs and InDels. We also conducted transcriptome sequencing to identify differentially expressed genes (DEGs) between zws-ms and zws-217.

RESULTS

Genetic analysis using the ED algorithm identified three SNP- and two InDel-associated regions for the multi-silique trait. Two highly overlapped parts of the SNP- and InDel-associated regions were identified as important intersecting regions, which are located on chromosomes A09 and C08, respectively, including 2044 genes in 10.20-MB length totally. Transcriptome sequencing revealed 129 DEGs between zws-ms and zws-217 in buds, including 39 DEGs located in the two abovementioned associated regions. We identified candidate genes involved in multi-silique formation in rapeseed based on the results of functional annotation.

CONCLUSIONS

This study identified the genomic regions and candidate genes related to the multi-silique trait in rapeseed.

Yield performance of early-season rice cultivars grown in the late season of double-season crop production under machine-transplanted conditions

In order to solve the problem of labor shortage in double-season rice production areas, machine transplanting, as opposed to manual transplanting, has become the more popular alternative method in rice cultivation. However, the most existing late rice cultivars are not suitable for machine double-season rice cultivation due to their long duration of growth. Therefore, based on the previous studies we chose early season rice cultivars to meet the needs of machine double-season rice cultivation. In this study, field experiments were conducted during the late season in 2015 and 2016 in Liuyang County, Hunan Province, China. Grain yield and yield-related traits were compared among eight early-season cultivars (Liangyou 6, Lingliangyou 211, Lingliangyou 268, Zhuliangyou 819, Xiangzaoxian 32, Xiangzaoxian 42, Zhongjiazao 17, and Zhongzao 39) in 2015 and four cultivars (Lingliangyou 268, Zhuliangyou 819, Zhongjiazao 17, and Zhongzao 39) in 2016, selected from the highest yielding cultivars grown in 2015. Lingliangyou 268 produced 8-44% higher grain yield than did the other cultivars except Zhongjiazao17 in 2015. This higher grain yield was driven by grain weight and aboveground biomass. The greater aboveground biomass in Lingliangyou 268 was mainly attributed to higher apparent radiation use efficiency (aboveground biomass/incident solar radiation). Our study suggests that improvement in grain weight and apparent radiation use efficiency were critical to the high grain yield of early-season rice cultivars grown in late season under machine transplanting conditions.

Whole Genome Resequencing from Bulked Populations as a Rapid QTL and Gene Identification Method in Rice

Most Quantitative Trait Loci (QTL) and gene isolation approaches, such as positional- or map-based cloning, are time-consuming and low-throughput methods. Understanding and detecting the genetic material that controls a phenotype is a key means to functionally analyzing genes as well as to enhance crop agronomic traits. In this regard, high-throughput technologies have great prospects for changing the paradigms of DNA marker revealing, genotyping, and for discovering crop genetics and genomic study. Bulk segregant analysis, based on whole genome resequencing approaches, permits the rapid isolation of the genes or QTL responsible for the causative mutation of the phenotypes. MutMap, MutMap Gap, MutMap+, modified MutMap, and QTL-seq methods are among those approaches that have been confirmed to be fruitful gene mapping approaches for crop plants, such as rice, irrespective of whether the characters are determined by polygenes. As a result, in the present study we reviewed the progress made by all these methods to identify QTL or genes in rice.

Genetic mapping of anthocyanin accumulation-related genes in pepper fruits using a combination of SLAF-seq and BSA

Anthocyanins have significant functions in stress tolerance in pepper (Capsicum annuum L.) and also benefit human health. Nevertheless, the key structural genes and regulatory genes involved in anthocyanin accumulation in pepper fruits are still not well understood and fine mapped. For the present study, 383 F₂ plants from a cross between the green-fruited C. annuum line Z5 and the purple-fruited line Z6 was developed. Two separate bulked DNA pools were constructed with DNAs extracted from either 37 plants with high anthocyanin content or from 18 plants with no anthocyanin. A combination of specific-locus amplified fragment sequencing (SLAF-seq) and bulked segregant analysis (BSA) was used to identify candidates for regions associated with anthocyanin accumulation. We identified a total of 127,004 high-quality single nucleotide polymorphism (SNP) markers, and detected 1674 high-quality SNP markers associated with anthocyanin accumulation. Three candidate anthocyanin-associated regions including the intervals from 12.48 to 20.00 Mb, from 54.67 to 56.59 Mb, and from 192.17 to 196.82 Mb were identified within a 14.10-Mb interval on chromosome 10 containing 126 candidate genes. Based on their annotations, we identified 12 candidate genes that are predicted to be associated with anthocyanin expression. The present results provide an efficient strategy for genetic mapping of and valuable insights into the genetic mechanisms of anthocyanin accumulation in pepper fruit, and allow us to clone and functionally analyze the genes that influence anthocyanin accumulation in this species.

QTL-Seq-based genetic analysis identifies a major genomic region governing dwarfness in rice (Oryza sativa L.)

A major dwarfing region for plant height, asd1, was identified employing the next-generation sequencing-based QTL-Seq approach from a dwarf mutant and is demonstrated to be responsible for the dwarf nature with least penalty on yield in rice. The yield plateauing of modern rice is witnessed since many decades due to the narrow genetic base owing to the usage of a single recessive gene, i.e., semi-dwarf-1 (sd-1) for development of short-statured varieties throughout the world. This calls for the searching of alternate sources for short stature in rice. To this end, we made an attempt to uncover yet another, but valuable dwarfing gene employing next-generation sequencing (NGS)-based QTL-Seq approach. Here, we have identified a major QTL governing plant height on chromosome 1, i.e., alternate semi-dwarf 1 (asd1) from an F₂ mapping population derived from a cross between a dwarf mutant, LND384, and a tall landrace, INRC10192. Fine mapping of asd1 region employing sequence-based indel markers delimited the QTL region to 67.51 Kb. The sequencing of the QTL region and gene expression analysis predicted a gene that codes for IWS1 (C-terminus family protein). Furthermore, marker-assisted introgression of the asd1 into tall landrace, INRC10192, reduced its plant height substantially while least affecting the yield and its component traits. Hence, this novel dwarfing gene, asd1, has profound implications in rice breeding.

Candidate genes for first flower node identified in pepper using combined SLAF-seq and BSA

First flower node (FFN) is an important trait for evaluating fruit earliness in pepper (Capsicum annuum L.), but the genetic mechanisms that control FFN are still poorly understood. In the present study, we developed 249 F₂ plants derived from an intraspecific cross between the inbred pepper lines Z4 and Z5. Thirty plants with the highest FFN and 30 plants with the lowest FFN were chosen and their DNAs were pooled according to phenotype to construct two bulked DNA pools. Specific-locus amplified fragment sequencing (SLAF-seq) was combined with bulked segregant analysis (BSA) to identify candidate regions related to FFN. According to our genetic analysis, the FFN trait is quantitatively inherited. A total of 106,848 high-quality single nucleotide polymorphism (SNP) markers were obtained, and 393 high-quality SNP markers associated with FFN were detected. Ten candidate regions within an interval of 3.98 Mb on chromosome 12 harboring 23 candidate genes were identified as closely correlated with FFN. Five genes (CA12g15130, CA12g15160, CA12g15370, CA12g15360, and CA12g15390) are predicted based on their annotations to be associated with expression of the FFN trait. The present study demonstrates an efficient genetic mapping strategy and lays a good foundation for molecular marker-assisted breeding using SNP markers linked to FFN and for cloning and functional analysis of the key genes controlling FFN.

Toward Identification of Black Lemma and Pericarp Gene Blp1 in Barley Combining Bulked Segregant Analysis and Specific-Locus Amplified Fragment Sequencing

Black barley is caused by phytomelanin synthesized in lemma and/or pericarp and the trait is controlled by one dominant gene Blp1. The gene is mapped on chromosome 1H by molecular markers, but it is yet to be isolated. Specific-locus amplified fragment sequencing (SLAF-seq) is an effective method for large-scale de novo single nucleotide polymorphism (SNP) discovery and genotyping. In the present study, SLAF-seq with bulked segregant analysis (BSA) was employed to obtain sufficient markers to fine mapping Blp1 gene in an F2 population derived from Hatiexi No.1 × Zhe5819. Based on SNP screening criteria, a total of 77,542 polymorphic SNPs met the requirements for association analysis. Combining two association analysis methods, the overlapped region with a size of 32.41 Mb on chromosome 1H was obtained as the candidate region of Blp1 gene. According to SLAF-seq data, markers were developed in the target region and were used for mapping the Blp1 gene. Linkage analysis showed that Blp1 co-segregated with HZSNP34 and HZSNP36, and was delimited by two markers (HZSNP35 and HZSNP39) spanning 8.1 cM in 172 homozygous yellow grain F2 plants of Hatiexi No.1 × Zhe5819. More polymorphic markers were screened in the reduced target region and were used to genotype the population. As a result, Blp1 was delimited within a 1.66 Mb on chromosome 1H by the upstream marker HZSNP63 and the downstream marker HZSNP59. Our results demonstrated the utility of SLAF-seq-BSA approach to identify the candidate region and discover polymorphic markers at the specific targeted genomic region.

Rapid identification of QTLs underlying resistance to Cucumber mosaic virus in pepper (Capsicum frutescens)

Next-generation sequencing enabled a fast discovery of QTLs controlling CMV resistant in pepper. The gene CA02g19570 as a possible candidate gene of qCmr2.1 was identified for resistance to CMV in pepper. Cucumber mosaic virus (CMV) is one of the most important viruses infecting pepper, but the genetic basis of CMV resistance in pepper is elusive. In this study, we identified a candidate gene for CMV resistance QTL, qCmr2.1 through SLAF-seq. Segregation analysis in F₂, BC₁ and F_2:3 populations derived from a cross between two inbred lines 'PBC688' (CMV-resistant) and 'G29' (CMV-susceptible) suggested quantitative inheritance of resistance to CMV in pepper. Genome-wide comparison of SNP profiles between the CMV-resistant and CMV-susceptible bulks constructed from an F₂ population identified two QTLs, designated as qCmr2.1 on chromosome 2 and qCmr11.1 on chromosome 11 for resistance to CMV in PBC688, which were confirmed by InDel marker-based classical QTL mapping in the F₂ population. As a major QTL, joint SLAF-seq and traditional QTL analysis delimited qCmr2.1 to a 330 kb genomic region. Two pepper genes, CA02g19570 and CA02g19600, were identified in this region, which are homologous with the genes LOC104113703, LOC104248995, LOC102603934 and LOC101248357, which were predicted to encode N-like protein associated with TMV-resistant in Solanum crops. Quantitative RT-PCR revealed higher expression levels of CA02g19570 in CMV resistance genotypes. The CA02g19600 did not exhibit obvious regularity in expression patterns. Higher relative expression levels of CA02g19570 in PBC688 and F₁ were compared with those in G29 during days after inoculation. These results provide support for CA02g19570 as a possible candidate gene of qCmr2.1 for resistance to CMV in pepper.

A Highly Dense Genetic Map for Ginkgo biloba Constructed Using Sequence-Based Markers

Ginkgo biloba L. is a well-known living gymnosperm fossil that has medicinal and ornamental value. In this study, a high density genetic map was constructed with megagametophytes of 94 seeds from a single Ginkgo tree by employing the specific-locus amplified fragment (SLAF) sequencing technique. The average sequencing depth was 11.20×, which yielded 538,031 high-quality SLAFs. Among these SLAFs, 204,361 were heterozygous in the maternal tree and segregated in the progeny. The established map contained 12,263 SLAFs that were assigned to 12 linkage groups (LGs). The number of LGs on this map equaled the number of chromosomes in Ginkgo. The total map length was 1,671.77 cM, with an average distance of 0.89 cM between adjacent marker bins. Map evaluation based on the haplotype map and the heat map validated the high quality of the established map. Because Ginkgo is an economically and biologically important tree, strenuous efforts have been exerted to sequence its genome. This new map, built using sequence-based markers, will serve in the future as a fundamental platform for anchoring sequence assemblies along Ginkgo chromosomes. This map also provides a desirable platform for various genetic studies of Ginkgo, including gene/quantitative trait locus mapping and marker-aided selection.

Marker development using SLAF-seq and whole-genome shotgun strategy to fine-map the semi-dwarf gene ari-e in barley

Background

Barley semi-dwarf genes have been extensively explored and widely used in barley breeding programs. The semi-dwarf gene ari-e from Golden Promise is an important gene associated with some agronomic traits and salt tolerance. While ari-e has been mapped on barley chromosome 5H using traditional markers and next-generation sequencing technologies, it has not yet been finely located on this chromosome.

Results

We integrated two methods to develop molecular markers for fine-mapping the semi-dwarf gene ari-e: (1) specific-length amplified fragment sequencing (SLAF-seq) with bulked segregant analysis (BSA) to develop SNP markers, and (2) the whole-genome shotgun sequence to develop InDels. Both SNP and InDel markers were developed in the target region and used for fine-mapping the ari-e gene. Linkage analysis showed that ari-e co-segregated with marker InDel-17 and was delimited by two markers (InDel-16 and DGSNP21) spanning 6.8 cM in the doubled haploid (DH) Dash × VB9104 population. The genetic position of ari-e was further confirmed in the Hindmarsh × W1 DH population which was located between InDel-7 and InDel-17. As a result, the overlapping region of the two mapping populations flanked by InDel-16 and InDel-17 was defined as the candidate region spanning 0.58 Mb on the POPSEQ physical map.

Conclusions

The current study demonstrated the SLAF-seq for SNP discovery and whole-genome shotgun sequencing for InDel development as an efficient approach to map complex genomic region for isolation of functional gene. The ari-e gene was fine mapped from 10 Mb to 0.58 Mb interval.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-3247-4) contains supplementary material, which is available to authorized users.

Identification and Validation of SNP Markers Linked to Dwarf Traits Using SLAF-Seq Technology in Lagerstroemia

The genetic control of plant architecture is a promising approach to breed desirable cultivars, particularly in ornamental flowers. In this study, the F1 population (142 seedlings) derived from Lagerstroemia fauriei (non-dwarf) × L. indica 'Pocomoke' (dwarf) was phenotyped for six traits (plant height (PH), internode length (IL), internode number, primary lateral branch height (PLBH), secondary lateral branch height and primary branch number), and the IL and PLBH traits were positively correlated with the PH trait and considered representative indexes of PH. Fifty non-dwarf and dwarf seedlings were pooled and subjected to a specific-locus amplified fragment sequencing (SLAF-seq) method, which screened 1221 polymorphic markers. A total of 3 markers segregating between bulks were validated in the F1 population, with the M16337 and M38412 markers highly correlated with the IL trait and the M25207 marker highly correlated with the PLBH trait. These markers provide a predictability of approximately 80% using a single marker (M25207) and a predictability of 90% using marker combinations (M16337 + M25207) in the F1 population, which revealed that the IL and the PLBH traits, especially the PLBH, were the decisive elements for PH in terms of molecular regulation. Further validation was performed in the BC1 population and a set of 28 Lagerstroemia stocks using allele-specific PCR (AS-PCR) technology, and the results showed the stability and reliability of the SNP markers and the co-determination of PH by multiple genes. Our findings provide an important theoretical and practical basis for the early prediction and indirect selection of PH using the IL and the PLBH, and the detected SNPs may be useful for marker-assisted selection (MAS) in crape myrtle.

Construction of the first high-density genetic linkage map of Salvia miltiorrhiza using specific length amplified fragment (SLAF) sequencing

Salvia miltiorrhiza is an important medicinal crop in traditional Chinese medicine (TCM). Knowledge of its genetic foundation is limited because sufficient molecular markers have not been developed, and therefore a high-density genetic linkage map is incomplete. Specific length amplified fragment sequencing (SLAF-seq) is a recently developed high-throughput strategy for large-scale SNP (Single Nucleotide Polymorphisms) discovery and genotyping based on next generation sequencing (NGS). In this study, genomic DNA extracted from two parents and their 96 F1 individuals was subjected to high-throughput sequencing and SLAF library construction. A total of 155.96 Mb of data containing 155,958,181 pair-end reads were obtained after preprocessing. The average coverage of each SLAF marker was 83.43-fold for the parents compared with 10.36-fold for the F1 offspring. The final linkage map consists of 5,164 SLAFs in 8 linkage groups (LGs) and spans 1,516.43 cM, with an average distance of 0.29 cM between adjacent markers. The results will not only provide a platform for mapping quantitative trait loci but also offer a critical new tool for S. miltiorrhiza biotechnology and comparative genomics as well as a valuable reference for TCM studies.

Mapping of a Novel Race Specific Resistance Gene to Phytophthora Root Rot of Pepper (Capsicum annuum) Using Bulked Segregant Analysis Combined with Specific Length Amplified Fragment Sequencing Strategy

Phytophthora root rot caused by Phytophthora capsici (P. capsici) is a serious limitation to pepper production in Southern China, with high temperature and humidity. Mapping PRR resistance genes can provide linked DNA markers for breeding PRR resistant varieties by molecular marker-assisted selection (MAS). Two BC1 populations and an F2 population derived from a cross between P. capsici-resistant accession, Criollo de Morelos 334 (CM334) and P. capsici-susceptible accession, New Mexico Capsicum Accession 10399 (NMCA10399) were used to investigate the genetic characteristics of PRR resistance. PRR resistance to isolate Byl4 (race 3) was controlled by a single dominant gene, PhR10, that was mapped to an interval of 16.39Mb at the end of the long arm of chromosome 10. Integration of bulked segregant analysis (BSA) and Specific Length Amplified Fragment sequencing (SLAF-seq) provided an efficient genetic mapping strategy. Ten polymorphic Simple Sequence Repeat (SSR) markers were found within this region and used to screen the genotypes of 636 BC1 plants, delimiting PhR10 to a 2.57 Mb interval between markers P52-11-21 (1.5 cM away) and P52-11-41 (1.1 cM). A total of 163 genes were annotated within this region and 31 were predicted to be associated with disease resistance. PhR10 is a novel race specific gene for PRR, and this paper describes linked SSR markers suitable for marker-assisted selection of PRR resistant varieties, also laying a foundation for cloning the resistance gene.

Rapid Identification of Candidate Genes for Seed Weight Using the SLAF-Seq Method in Brassica napus

Seed weight is a critical and direct trait for oilseed crop seed yield. Understanding its genetic mechanism is of great importance for yield improvement in Brassica napus breeding. Two hundred and fifty doubled haploid lines derived by microspore culture were developed from a cross between a large-seed line G-42 and a small-seed line 7–9. According to the 1000-seed weight (TSW) data, the individual DNA of the heaviest 46 lines and the lightest 47 lines were respectively selected to establish two bulked DNA pools. A new high-throughput sequencing technology, Specific Locus Amplified Fragment Sequencing (SLAF-seq), was used to identify candidate genes of TSW in association analysis combined with bulked segregant analysis (BSA). A total of 1,933 high quality polymorphic SLAF markers were developed and 4 associated markers of TSW were procured. A hot region of ~0.58 Mb at nucleotides 25,401,885–25,985,931 on ChrA09 containing 91 candidate genes was identified as tightly associated with the TSW trait. From annotation information, four genes (GSBRNA2T00037136001, GSBRNA2T00037157001, GSBRNA2T00037129001 and GSBRNA2T00069389001) might be interesting candidate genes that are highly related to seed weight.

Cloning and Characterization of TaTGW-7A Gene Associated with Grain Weight in Wheat via SLAF-seq-BSA

Thousand-grain weight (TGW) of wheat (Triticum aestivum L.) contributes significantly to grain yield. In the present study, a candidate gene associated with TGW was identified through specific-locus amplified fragment sequencing (SLAF-seq) of DNA bulks of recombinant inbred lines (RIL) derived from the cross between Jing 411 and Hongmangchun 21. The gene was located on chromosome 7A, designated as TaTGW-7A with a complete genome sequence and an open reading frame (ORF). A single nucleotide polymorphism (SNP) was present in the first exon between two alleles at TaTGW-7A locus, resulting in a Val to Ala substitution, corresponding to a change from higher to lower TGW. Cleaved amplified polymorphic sequence (CAPS) (TGW7A) and InDel (TG9) markers were developed to discriminate the two alleles TaTGW-7Aa and TaTGW-7Ab for higher and lower TGW, respectively. A major QTL co-segregating with TaTGW-7A explained 21.7-27.1% of phenotypic variance for TGW in the RIL population across five environments. The association of TaTGW-7A with TGW was further validated in a natural population and Chinese mini-core collections. Quantitative real-time PCR revealed higher transcript levels of TaTGW-7Aa than those of TaTGW-7Ab during grain development. High frequencies of the superior allele TaTGW-7Aa for higher TGW in Chinese mini-core collections (65.0%) and 501 wheat varieties (86.0%) indicated a strong and positive selection of this allele in wheat breeding. The molecular markers TGW7A and TG9 can be used for improvement of TGW in breeding programs.

Genome-Wide Association Study of Grain Appearance and Milling Quality in a Worldwide Collection of Indica Rice Germplasm

Grain appearance quality and milling quality are the main determinants of market value of rice. Breeding for improved grain quality is a major objective of rice breeding worldwide. Identification of genes/QTL controlling quality traits is the prerequisite for increasing breeding efficiency through marker-assisted selection. Here, we reported a genome-wide association study in indica rice to identify QTL associated with 10 appearance and milling quality related traits, including grain length, grain width, grain length to width ratio, grain thickness, thousand grain weight, degree of endosperm chalkiness, percentage of grains with chalkiness, brown rice rate, milled rice rate and head milled rice rate. A diversity panel consisting of 272 indica accessions collected worldwide was evaluated in four locations including Hangzhou, Jingzhou, Sanya and Shenzhen representing indica rice production environments in China and genotyped using genotyping-by-sequencing and Diversity Arrays Technology based on next-generation sequencing technique called DArTseq™. A wide range of variation was observed for all traits in all environments. A total of 16 different association analysis models were compared to determine the best model for each trait-environment combination. Association mapping based on 18,824 high quality markers yielded 38 QTL for the 10 traits. Five of the detected QTL corresponded to known genes or fine mapped QTL. Among the 33 novel QTL identified, qDEC1.1 (qGLWR1.1), qBRR2.2 (qGL2.1), qTGW2.1 (qGL2.2), qGW11.1 (qMRR11.1) and qGL7.1 affected multiple traits with relatively large effects and/or were detected in multiple environments. The research provided an insight of the genetic architecture of rice grain quality and important information for mining genes/QTL with large effects within indica accessions for rice breeding.

Characterization and fine mapping of a novel barley Stage Green-Revertible Albino Gene (HvSGRA) by Bulked Segregant Analysis based on SSR assay and Specific Length Amplified Fragment Sequencing

Background

Leaf color variations are common in plants. Herein we describe a natural mutant of barley cultivar Edamai No.6, whs18, whose leaf color showed stable and inheritable stage-green-revertible-albino under field condition.

Methods

Bulked Segregant Analysis (BSA) based on SSR assay and Specific Length Amplified Fragment Sequencing (SLAF-seq) was used to map the candidate gene for this trait.

Results

We found that leaf color of whs18 was green at seedling stage, while the seventh or eighth leaf began to show etiolation, and albino leaves emerged after a short period. The newly emerged leaves began to show stripe white before jointing stage, and normal green leaves emerged gradually. The duration of whs18 with abnormal leaf color lasted for about 3 months, which had some negative impacts on yield-related-traits. Further investigations showed that the variation was associated with changes in chlorophyII content and chloroplast development. Genetic analysis revealed that the trait was controlled by a single recessive nuclear gene, and was designed as HvSGRA in this study. Based on the F₂ population derived from Edamai No.9706 and whs18, we initially mapped the HvSGRA gene on the short arm of chromosome 2H using SSR and BSA. GBMS247 on 2HS showed co-segregation with HvSGRA. The genetic distance between the other marker GBM1187 and HvSGRA was 1.2 cM. Further analysis using BSA with SLAF-seq also identified this region as candidate region. Finally, HvSGRA interval was narrowed to 0.4 cM between morex_contig_160447 and morex_contig_92239, which were anchored to two adjacent FP contigs, contig_34437 and contig_46434, respectively. Furthermore, six putative genes with high-confidence in this interval were identified by POPSEQ. Further analysis showed that the substitution from C to A in the third exon of fructokinase-1-like gene generated a premature stop codon in whs18, which may lead to loss function of this gene.

Conclusions

Using SSR and SLAF-seq in conjunction with BSA, we mapped HvSGRA within two adjacent FP contigs of barley. The mutation of fructokinase-1-like gene in whs18 may cause the stage green-revertible albino of barley. The current study lays foundation for hierarchical map-based cloning of HvSGRA and utilizing the gene/trait as a visualized maker in molecular breeding in future.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-2015-1) contains supplementary material, which is available to authorized users.

Genetic characteristics of soybean resistance to HG type 0 and HG type 1.2.3.5.7 of the cyst nematode analyzed by genome-wide association mapping

BACKGROUND

Soybean cyst nematode (SCN, Heterodera glycines Ichinohe) is one of the most fatal pests of soybean (Glycine max (L.) Merr.) worldwide and causes huge loss of soybean yield each year. Multiple sources of resistance are urgently needed for effective management of SCN via the development of resistant cultivars. The aim of the present study was to investigate the genetic architecture of resistance to SCN HG Type 0 (race 3) and HG Type 1.2.3.5.7 (race 4) in landraces and released elite soybean cultivars mostly from China.

RESULTS

A total of 440 diverse soybean landraces and elite cultivars were screened for resistance to SCN HG Type 0 and HG Type 1.2.3.5.7. Exactly 131 new sources of SCN resistance were identified. Lines were genotyped by SNP markers detected by the Specific Locus Amplified Fragment Sequencing (SLAF-seq) approach. A total of 36,976 SNPs were identified with minor allele frequencies (MAF) > 4% that were present in 97% of all the genotypes. Genome-wide association mapping showed that a total of 19 association signals were significantly related to the resistance for the two HG Types. Of the 19 association signals, eight signals overlapped with reported QTL including Rhg1 and Rhg4 genes. Another eight were located in the linked regions encompassing known QTL. Three QTL were found that were not previously reported. The average value of female index (FI) of soybean accessions with resistant alleles was significantly lower than those with susceptible alleles for each peak SNP. Disease resistance proteins with leucine rich regions, cytochrome P450s, protein kinases, zinc finger domain proteins, RING domain proteins, MYB and WRKY transcription activation families were identified. Such proteins may participate in the resistant reaction to SCN and were frequently found in the tightly linked genomic regions of the peak SNPs.

CONCLUSIONS

GWAS extended understanding of the genetic architecture of SCN resistance in multiple genetic backgrounds. Nineteen association signals were obtained for the resistance to the two Hg Types of SCN. The multiple beneficial alleles from resistant germplasm sources will be useful for the breeding of cultivars with improved resistance to SCN. Analysis of genes near association signals may facilitate the recognition of the causal gene(s) underlying SCN resistances.