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Author(s):  
Ravi Koppolu ◽  
Guojing Jiang ◽  
Sara G. Milner ◽  
Quddoos H. Muqaddasi ◽  
Twan Rutten ◽  
...  

Abstract Key message Spikelet indeterminacy and supernumerary spikelet phenotypes in barley multiflorus2.b mutant show polygenic inheritance. Genetic analysis of multiflorus2.b revealed major QTLs for spikelet determinacy and supernumerary spikelet phenotypes on 2H and 6H chromosomes. Abstract Understanding the genetic basis of yield forming factors in small grain cereals is of extreme importance, especially in the wake of stagnation of further yield gains in these crops. One such yield forming factor in these cereals is the number of grain-bearing florets produced per spikelet. Wild-type barley (Hordeum vulgare L.) spikelets are determinate structures, and the spikelet axis (rachilla) degenerates after producing single floret. In contrast, the rachilla of wheat (Triticum ssp.) spikelets, which are indeterminate, elongates to produce up to 12 florets. In our study, we characterized the barley spikelet determinacy mutant multiflorus2.b (mul2.b) that produced up to three fertile florets on elongated rachillae of lateral spikelets. Apart from the lateral spikelet indeterminacy (LS-IN), we also characterized the supernumerary spikelet phenotype in the central spikelets (CS-SS) of mul2.b. Through our phenotypic and genetic analyses, we identified two major QTLs on chromosomes 2H and 6H, and two minor QTLs on 3H for the LS-IN phenotype. For, the CS-SS phenotype, we identified one major QTL on 6H, and a minor QTL on 5H chromosomes. Notably, the 6H QTLs for CS-SS and LS-IN phenotypes co-located with each other, potentially indicating that a single genetic factor might regulate both phenotypes. Thus, our in-depth phenotyping combined with genetic analyses revealed the quantitative nature of the LS-IN and CS-SS phenotypes in mul2.b, paving the way for cloning the genes underlying these QTLs in the future.


Rice ◽  
2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Dachuan Wang ◽  
Kai Zhou ◽  
Siqian Xiang ◽  
Qiuli Zhang ◽  
Ruxiang Li ◽  
...  

Abstract Background Seed-set density is an important agronomic trait in rice. However, its genetic mechanism is complex. Chromosome segment substitution lines (CSSLs) are ideal materials for studying complex traits. Results A rice CSSL, Z749, with a dense and erect panicle phenotype, was identified among progeny of the recipient parent Nipponbare and the donor parent Xihui 18. Z749 carried seven substitution segments (average length 2.12 Mb). Compared with Nipponbare, Z749 showed significant increases in the numbers of primary (NPB) and secondary branches (NSB), number of spikelets (SPP) and grains per panicle (GPP), seed-set density (SSD), and decrease in panicle length (PL). A secondary F2 population derived from a cross between Nipponbare and Z749 was used to map quantitative trait loci (QTLs) for associated traits. Fifteen QTLs distributed on chromosomes 5, 7, 8, and 10 were detected. The QTL qPL7 might be an allele of OsFAD8 and the remaining 14 QTLs (e.g., qSSD5 and qSSD10 etc.) might be novel. Fourteen QTLs were verified using five single-segment substitution lines (SSSLs). The seed-set density of Z749 was controlled predominantly by one major QTL (qSSD10) and two minor QTLs (qSSD5 and qSSD8). The QTLs qSSD10, qSSD5, and qSSD8 were fine-mapped to intervals of 1.05, 1.46, and 1.53 Mb on chromosomes 10, 5, and 8, respectively. Analysis of QTL additive effects indicated that qSSD5, qSSD8, and qSSD10 from Xihui18 increased seed-set density of Z749 by 14.10, 11.38, and 5.11 spikelets per 10 cm panicle, respectively. Analysis of QTL epistatic effects revealed that pyramiding of qSSD5 and qSSD8, qSSD5 and qSSD10, qSSD8 and qSSD10, and qSSD5, qSSD8 and qSSD10 produced novel genotypes with increased seed-set density. Conclusions Inheritance of seed-set density in Z749 was controlled predominantly by one major QTL (qSSD10) and two minor QTLs (qSSD5 and qSSD8). Then, they were fine-mapped to intervals of 1.05, 1.46, and 1.53 Mb on chromosomes 10, 5, 8, respectively. Two MAPK genes (OsMPK9 and OsMPK17) and one gene (candidate gene 6) involved in auxin metabolism might be candidate genes for qSSD5, and OsSAUR32 might be the candidate gene for qSSD8. Pyramiding of qSSD5, qSSD8, and qSSD10 enhanced seed-set density.


2021 ◽  
Author(s):  
Ravi Koppolu ◽  
Guojing Jiang ◽  
Sara G Milner ◽  
Quddoos H Muqaddasi ◽  
Twan Rutten ◽  
...  

AbstractUnderstanding the genetic basis of yield forming factors in small grain cereals is of extreme importance, especially in the wake of stagnation of further yield gains in these crops. One such yield forming factor in these cereals is the number of grain-bearing florets produced per spikelet. Wildtype barley (Hordeum vulgare L.) spikelets are determinate structures, the spikelet axis (rachilla) degenerates after producing single floret. In contrast, the rachilla of wheat (Triticum ssp.) spikelets, which are indeterminate, elongates to produce up to 12 florets. In our study, we characterized the barley spikelet determinacy mutant multiflorus2.b (mul2.b) that produced up to three fertile florets on elongated rachillae of lateral spikelets. Apart from the lateral spikelet indeterminacy (LS-IN), we also characterized the supernumerary spikelet phenotype in the central spikelets (CS-SS) of mul2.b. Through our phenotypic and genetic analyses, we identified two major QTLs on chromosomes 2H and 6H, and two minor QTLs on 3H for the LS-IN phenotype. For, the CS-SS phenotype we identified one major QTL on 6H, and a minor QTL on 5H chromosomes. Notably, the 6H QTLs for CS-SS and LS-IN phenotypes co-located with each other, potentially indicating that a single genetic factor might regulate both phenotypes. Thus, our in-depth phenotyping combined with genetic analyses revealed the quantitative nature of the LS-IN and CS-SS phenotypes in mul2.b, paving the way for cloning the genes underlying these QTLs in the future.Key messageSpikelet indeterminacy and supernumerary spikelet phenotypes in barley multiflorus2.b mutant show polygenic inheritance. Genetic analysis of multiflorus2.b revealed major QTLs for spikelet determinacy and supernumerary spikelet phenotypes on 2H and 6H chromosomes.


2021 ◽  
Author(s):  
Dachuan Wang ◽  
Kai Zhou ◽  
Siqian Xiang ◽  
Qiuli Zhang ◽  
Ruxiang Li ◽  
...  

Abstract Background Seed-set density is an important agronomic trait in rice. However, its genetic mechanism is complex. Chromosome segment substitution lines (CSSLs) are ideal materials for studying complex traits. Results A rice CSSL, Z749, with a dense and erect panicle phenotype, was identified among progeny of the recipient parent Nipponbare and the donor parent Xihui 18. Z749 carried seven substitution segments (average length 2.16 Mb). Compared with Nipponbare, Z749 showed significant increases in the numbers of primary (NPB) and secondary branches (NSB), number of spikelets (SPP) and grains per panicle (GPP), seed-set density (SSD), and decrease in panicle length (PL). A secondary F2 population derived from a cross between Nipponbare and Z749 was used to map quantitative trait loci (QTLs) for associated traits. Fifteen QTLs distributed on chromosomes 5, 7, 8, and 10 were detected. The QTL qPL7 might be an allele of OsFAD8 and the remaining 14 QTLs (e.g., qSSD5 and qSSD10 etc.) might be novel. Fourteen QTLs were verified using five single-segment substitution lines (SSSLs). The seed-set density of Z749 was controlled predominantly by one major QTL (qSSD10) and two minor QTLs (qSSD5 and qSSD8). The QTLs qSSD10, qSSD5, and qSSD8 were fine-mapped to intervals of 1.05, 1.46, and 1.53 Mb on chromosomes 10, 5, and 8, respectively. Analysis of QTL additive effects indicated that qSSD5, qSSD8, and qSSD10 from Xihui18 increased seed-set density of Z749 by 14.1, 11.38, and 5.11 spikelets per 10 cm panicle, respectively. Analysis of QTL epistatic effects revealed that pyramiding of qSSD5 and qSSD8, qSSD5 and qSSD10, qSSD8 and qSSD10, and qSSD5, qSSD8 and qSSD10 produced novel genotypes with increased seed-set density. Conclusions Inheritance of seed-set density in Z749 was controlled predominantly by one major QTL (qSSD10) and two minor QTLs (qSSD5 and qSSD8). Then, they were fine-mapped to intervals of 1.05, 1.46, and 1.53 Mb on chromosomes 10, 5, 8, respectively. Two MAPK genes (OsMPK9 and OsMPK17) and one gene (candidate gene 6) involved in auxin metabolism might be candidate genes for qSSD5, and OsSAUR32 might be the candidate gene for qSSD8. Pyramiding of qSSD5, qSSD8, and qSSD10 enhanced seed-set density.


2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Ryoma Takeshima ◽  
Eri Ogiso-Tanaka ◽  
Yasuo Yasui ◽  
Katsuhiro Matsui

Abstract Background Common 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. Results By 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. Conclusions We 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.


2020 ◽  
Author(s):  
Ishwarappa S. Katageri ◽  
S. Anjan Gowda ◽  
Prashanth B.N ◽  
Mahesh Biradar ◽  
Rajeev M ◽  
...  

Conventional breeding interventions in cotton have been successful and these techniques have doubled the productivity of cotton, but it took around 40 years. One of the techniques of molecular biology i.e., genetic engineering has brought significant improvement in productivity within the year of introduction. With cotton genomics maturing, many reference genomes and related genomic resources have been developed. Newer wild species have been discovered and many countries are conserving genetic resources within and between species. This valuable germplasm can be exchanged among countries for increasing cotton productivity. As many as 249 Mapping and Association studies have been carried out and many QTLs have been discovered and it is high time for researchers to get into fine-mapping studies. Techniques of genomic selection hold valuable trust for deciphering quantitative traits like fiber quality and productivity since they take in to account all minor QTLs. There are just two studies involving genomic selection in cotton, underlining its huge prospects in cotton research. Genome editing and transformation techniques have been widely used in cotton with as many as 65 events being developed across various characters, and eight studies carried out using crisper technology. These promising technologies have huge prospects for cotton production sustainability.


Author(s):  
Gaurav Khosla ◽  
B. S. Gill ◽  
Asmita Sirari ◽  
Pankaj Sharma ◽  
Inderpreet Dhaliwal

The variation for 100 seed weight in F2 population derived from a cross, AGS456 (an exotic vegetable type from Taiwan)/SL958 of soybean followed a normal curve with a range of 8.00-27.22g indicating quantitative nature of genetic control for seed size. Parental lines were screened with 207 SSR markers to identify polymorphism and 90 primer pairs detected polymorphism between the parents. These ninety markers were used for detecting polymorphism between two extreme bulks for seed weight. Out of these, 18 primer pairs were polymorphic for the bulks and were used for bulk segregant analysis in 200 F2 plants. One major QTL for seed weight was identified on LG M with Sat_244 and Satt175 as flanking markers, explaining 19.0 per cent phenotypic variation. Two minor QTLs were also identified on LG D1b, one in interval Satt041-Sat_069 with an estimated phenotypic variation (R2) of 6.0 per cent and the other in interval Sat_069-Sat_0183 estimating 7.0 per cent phenotypic variance. The markers flanking TLs may help in marker-assisted selection (MAS) for improvement of seed weight in soybean after fine mapping and validation.


Author(s):  
Aye Nyein Chan ◽  
Lin-Lin Wang ◽  
Yu-Jun Zhu ◽  
Ye-Yang Fan ◽  
Jie-Yun Zhuang ◽  
...  

Abstract Key message A minor QTL for grain weight in rice, qTGW1.2b, was fine-mapped. Its casual gene OsVQ4 was confirmed through CRISPR/Cas9-targeted mutagenesis, exhibiting an effect that was larger than the original QTL effect. Abstract The CRISPR/Cas system exhibits a great potential for rice improvement, but the application was severely hindered due to insufficient target genes, especial the lack of validated genes underlying quantitative trait loci having small effects. In this study, a minor QTL for grain weight, qTGW1.2b, was fine-mapped into a 44.0 kb region using seven sets of near isogenic lines (NILs) developed from the indica rice cross (Zhenshan 97)3/Milyang 46, followed by validation of the causal gene using CRISPR/Cas9-targeted mutagenesis. In the NIL populations, 1000-grain weight of the Zhenshan 97 homozygous lines decreased by 0.9–2.0% compared with the Milyang 46 homozygous lines. A gene encoding VQ-motif protein, OsVQ4, was identified as the candidate gene based on parental sequence differences. The effect of OsVQ4 was confirmed by creating CRISPR/Cas9 knockout lines, whose 1000-grain weight decreased by 2.8–9.8% compared with the wild-type transgenic line and the recipient. These results indicate that applying genome editing system could create novel alleles with large phenotypic variation at minor QTLs, which is an effective way to validate causal genes of minor QTLs. Our study establishes a strategy for cloning minor QTLs, which could also be used to identify a large number of potential target genes for the application of CRISPR/Cas system.


2020 ◽  
Author(s):  
Haichao Jiang ◽  
Yutao Feng ◽  
Lei Qiu ◽  
Guanjun Gao ◽  
Qinglu Zhang ◽  
...  

Abstract Background: Rice blast is an economically important and mutable disease of rice. Using host resistance gene to breed resistant varieties has been proven to be the most effective and economical method to control rice blast and new resistance genes or quantitative trait loci (QTLs) are then needed.Results: In this study, we constructed two advanced backcross population to mapping blast resistance QTLs. CR071 and QingGuAi3 were as the donor parent to establish two BC3F1 and derived BC3F2 backcross population in the Jin23B background. By challenging the two populations with natural infection in 2011 and 2012, 16 and 13 blast resistance QTLs were identified in Jin23B/CR071 and Jin23B/QingGuAi3 population, respectively. Among Jin23B/CR071 population, 3 major and 13 minor QTLs have explained the phenotypic variation from 3.50% to 34.08% in two years. And, among Jin23B/QingGuAi3 population, 2 major and 11 minor QTLs have explained the phenotypic variation from 2.42% to 28.95% in two years.Conclusions: Sixteen and thirteen blast resistance QTLs were identified in Jin23B/CR071 and Jin23B/QingGuAi3 population, respectively. QTL effect analyses suggested that major and minor QTLs interaction is the genetic basis for durable blast resistance in rice variety CR071 and QingGuAi3.


2020 ◽  
Author(s):  
Haichao Jiang ◽  
Yutao Feng ◽  
Lei Qiu ◽  
Guanjun Gao ◽  
Qinglu Zhang ◽  
...  

Abstract Background: Rice blast is an economically important and mutable disease of rice. Using host resistance gene to breed resistant varieties has been proven to be the most effective and economical method to control rice blast and new resistance genes or quantitative trait loci (QTLs) are then needed.Results: In this study, we constructed two advanced backcross population to mapping blast resistance QTLs. CR071 and QingGuAi were as the donor parent to establish two BC3F1 and derived BC3F2 backcross population in the Jin23B background. By challenging the two populations with natural infection in 2011 and 2012, 16 and 13 blast resistance QTLs were identified in Jin23B/CR071 and Jin23B/QingGuAi population, respectively. Among Jin23B/CR071 population, 3 major and 13 minor QTLs have explained the phenotypic variation from 3.50% to 34.08% during six observation times. And, among Jin23B/QingGuAi population, 2 major and 11 minor QTLs have explained the phenotypic variation from 2.42% to 28.95% during six observation times.Conclusions: Sixteen and thirteen blast resistance QTLs were identified in Jin23B/CR071 and Jin23B/QingGuAi population, respectively. QTL effect analyses suggested that major and minor QTLs interaction is the genetic basis for durable blast resistance in rice variety CR071 and QingGuAi.


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