Cloning Of Quantitative Trait Loci Research Articles

QTL Mapping for Agronomic Important Traits in Well-Adapted Wheat Cultivars

Wheat (Triticum aestivum L.) is one of the most important food crops worldwide and provides the staple food for 40% of the world’s population. Increasing wheat production has become an important goal to ensure global food security. The grain yield of wheat is a complex trait that is usually influenced by multiple agronomically important traits. Thus, the genetic dissection and discovery of quantitative trait loci (QTL) of wheat-yield-related traits are very important to develop high-yield cultivars to improve wheat production. To analyze the genetic basis and discover genes controlling important agronomic traits in wheat, a recombinant inbred lines (RILs) population consisting of 180 RILs derived from a cross between Xinong822 (XN822) and Yannong999 (YN999), two well-adapted cultivars, was used to map QTL for plant height (PH), spike number per spike (SNS), spike length (SL), grain number per spike (GNS), spike number per plant (SN), 1000- grain weight (TGW), grain length (GL), grain width (GW), length/width of grain (GL/GW), perimeter of grain (Peri), and surface area of grains (Sur) in three environments. A total of 64 QTL were detected and distributed on all wheat chromosomes except 3A and 5A. The identified QTL individually explained 2.24–38.24% of the phenotypic variation, with LOD scores ranging from 2.5 to 29. Nine of these QTL were detected in multiple environments, and seven QTL were associated with more than one trait. Additionally, Kompetitive Allele Specific PCR (KASP) assays for five major QTL QSns-1A.2 (PVE = 6.82), QPh-2D.1 (PVE = 37.81), QSl-2D (PVE = 38.24), QTgw-4B (PVE = 8.78), and QGns-4D (PVE = 13.54) were developed and validated in the population. The identified QTL and linked markers are highly valuable in improving wheat yield through marker-assisted breeding, and the large-effect QTL can be fine-mapped for further QTL cloning of yield-related traits in wheat.

QTG-Miner aids rapid dissection of the genetic base of tassel branch number in maize

Genetic dissection of agronomic traits is important for crop improvement and global food security. Phenotypic variation of tassel branch number (TBN), a major breeding target, is controlled by many quantitative trait loci (QTLs). The lack of large-scale QTL cloning methodology constrains the systematic dissection of TBN, which hinders modern maize breeding. Here, we devise QTG-Miner, a multi-omics data-based technique for large-scale and rapid cloning of quantitative trait genes (QTGs) in maize. Using QTG-Miner, we clone and verify seven genes underlying seven TBN QTLs. Compared to conventional methods, QTG-Miner performs well for both major- and minor-effect TBN QTLs. Selection analysis indicates that a substantial number of genes and network modules have been subjected to selection during maize improvement. Selection signatures are significantly enriched in multiple biological pathways between female heterotic groups and male heterotic groups. In summary, QTG-Miner provides a large-scale approach for rapid cloning of QTGs in crops and dissects the genetic base of TBN for further maize breeding.

Mapping and validation of quantitative trait loci associated with dorsal aleurone thickness in rice (Oryza sativa)

Mapping of QTLs for dorsal aleurone thickness (DAT) was performed using chromosome segment substitution lines in rice. Three QTLs, qDAT3.1, qDAT3.2, and qDAT7.1, were detected in multiple environments. As a specified endosperm cell type, the aleurone has an abundance of various nutrients. Increasing the number of aleurone layers is a practicable way of developing highly nutritious cereals. Identifying genes that can increase aleurone thickness is useful for the breeding of aleurone traits to improve the nutritional and health values of rice. Here, we found that iodine staining could efficiently distinguish the aleurone layers, which revealed great variation of the aleurone thickness in rice, especially at the dorsal side of the seed. Therefore, we used a population of chromosome segmental substitution lines (CSSLs) derived from Koshihikari and Nona Bokra for quantitative trait locus (QTL) analysis of the dorsal aleurone thickness (DAT). Three QTLs, qDAT3.1, qDAT3.2, and qDAT7.1, were detected in multiple seasons. Among these, qDAT3.2 colocalizes with Hd6 and Hd16, two QTLs previously identified to regulate the heading date of Koshihikari, explaining the negative correlation between the DAT and days to heading (DTH) in rice. We also provide evidence that early-heading ensures the filling of rice seed under a relatively high temperature to promote aleurone thickening. qDAT7.1, the most stable QTL expressed in different environments, functions independently from heading date. Although Nona Bokra has a lower DAT, its qDAT7.1 allele significantly increased DAT in rice, which was further validated using two near-isogenic lines (NILs). These findings pave the way for further gene cloning of aleurone-related QTLs and may aid the development of highly nutritious rice.

Comprehensive QTL analyses of nitrogen use efficiency in indica rice.

Nitrogen-use efficiency (NUE) in rice is a complex quantitative trait involved in multiple biological processes and agronomic traits; however, the genetic basis and regulatory network of NUE remain largely unknown. We constructed a high-resolution microarray-based genetic map for 261 recombinant inbred lines derived from two indica parents. Using 2,345 bin markers, comprehensive analyses of quantitative trait loci (QTLs) of seven key agronomic traits under two different N levels were performed. A total of 11 non-redundant QTLs for effective panicle number (EPN), 7 for grain number per panicle, 13 for thousand-grain weight, 2 for seed-setting percentage, 15 for plant height, 12 for panicle length, and 6 for grain yield per plant were identified. The QTL regions were as small as 512 kb on average, and more than half spanned an interval smaller than 100 kb. Using this advantage, we identified possible candidate genes of two major EPN-related QTLs. One QTL detected under both N levels possibly encodes a DELLA protein SLR1, which is known to regulate NUE, although the natural variations of this protein have not been reported. The other QTL detected only under a high N level could encode the transcription factor OsbZIP59. We also predicted the possible candidate genes for another three of the NUE-related QTLs. Our results provide a reference for improving NUE-related QTL cloning and promote our understanding of NUE regulation in indica rice.

Meta-QTL analysis and identification of candidate genes for quality, abiotic and biotic stress in durum wheat

The genetic improvement of durum wheat and enhancement of plant performance often depend on the identification of stable quantitative trait loci (QTL) and closely linked molecular markers. This is essential for better understanding the genetic basis of important agronomic traits and identifying an effective method for improving selection efficiency in breeding programmes. Meta-QTL analysis is a useful approach for dissecting the genetic basis of complex traits, providing broader allelic coverage and higher mapping resolution for the identification of putative molecular markers to be used in marker-assisted selection. In the present study, extensive QTL meta-analysis was conducted on 45 traits of durum wheat, including quality and biotic and abiotic stress-related traits. A total of 368 QTL distributed on all 14 chromosomes of genomes A and B were projected: 171 corresponded to quality-related traits, 127 to abiotic stress and 71 to biotic stress, of which 318 were grouped in 85 meta-QTL (MQTL), 24 remained as single QTL and 26 were not assigned to any MQTL. The number of MQTL per chromosome ranged from 4 in chromosomes 1A and 6A to 9 in chromosome 7B; chromosomes 3A and 7A showed the highest number of individual QTL (4), and chromosome 7B the highest number of undefined QTL (4). The recently published genome sequence of durum wheat was used to search for candidate genes within the MQTL peaks. This work will facilitate cloning and pyramiding of QTL to develop new cultivars with specific quantitative traits and speed up breeding programs.

Exploring genetic architecture for pod-related traits in soybean using image-based phenotyping.

The online version contains supplementary material available at 10.1007/s11032-021-01223-2.

Development of Chromosome Segment Substitution Lines (CSSLs) Derived from Guangxi Wild Rice (Oryza rufipogon Griff.) under Rice (Oryza sativa L.) Background and the Identification of QTLs for Plant Architecture, Agronomic Traits and Cold Tolerance.

Common wild rice contains valuable resources of novel alleles for rice improvement. It is well known that genetic populations provide the basis for a wide range of genetic and genomic studies. In particular, chromosome segment substitution lines (CSSLs) ais a powerful tool for fine mapping of quantitative traits, new gene discovery and marker-assisted breeding. In this study, 132 CSSLs were developed from a cultivated rice (Oryza sativa) cultivar (93-11) and common wild rice (Oryza rufipogon Griff. DP30) by selfing-crossing, backcrossing and marker-assisted selection (MAS). Based on the high-throughput sequencing of the 93-11 and DP30, 285 pairs of Insertion-deletions (InDel) markers were selected with an average distance of 1.23 Mb. The length of this DP30-CSSLs library was 536.4 cM. The coverage rate of substitution lines cumulatively overlapping the whole genome of DP30 was about 91.55%. DP30-CSSLs were used to analyze the variation for 17 traits leading to the detection of 36 quantitative trait loci (QTLs) with significant phenotypic effects. A cold-tolerant line (RZ) was selected to construct a secondary mapping F2 population, which revealed that qCT2.1 is in the 1.7 Mb region of chromosome 2. These CSSLs may, therefore, provide powerful tools for genome wide large-scale gene discovery in wild rice. This research will also facilitate fine mapping and cloning of QTLs and genome-wide study of wild rice. Moreover, these CSSLs will provide a foundation for rice variety improvement.

Mapping quantitative trait loci for disease resistance to false smut of rice

False smut of rice, an important emerging disease caused by Ustilaginoidea virens, greatly reduces grain yield and deteriorates grain quality in many rice-growing regions worldwide. Identification of quantitative trait loci (QTL) conferring false smut resistance will facilitate incorporation of false smut resistance into elite cultivars. In this study, a set of recombinant inbred lines (RILs) derived from a cross of a resistant rice landrace MR183–2 and a high susceptible line 08R2394 were evaluated to map resistance QTLs for false smut. A total of 179 simple sequence repeat (SSR) polymorphic markers were identified for constructing genetic linkage maps. Using a composite interval mapping method, five false smut resistance QTLs were detected on chromosomes 2, 4, 8 and 11 in the RIL population. Among these QTLs, qFsr8–1 within a small region on chromosome 8 represents a major quantitative locus explaining the greatest phenotypic variance. Gene annotation in this major QTL region provides a theoretical basis for cloning of resistance QTLs. The SSR markers genetically linked to qFsr8–1 are valuable for marker-assisted breeding for false smut resistance in rice. In addition, nine QTLs for heading date were detected in this population. Correlation analysis of disease resistance score and heading date indicates that false smut resistance negatively correlates with the growth period length in rice.

Identification of qLG2, qLG8, and qWG2 as novel quantitative trait loci for grain shape and the allelic analysis in cultivated rice.

Three novel QTLs for grain shape were genetically fine mapped, with two of which to a 250-kb target interval on rice chromosome 2 that contains fourteen candidate genes. Grain shape (grain length, width, and thickness) determines crop yield and grain quality. However, the trait is regulated by numerous naturally occurring quantitative trait loci (QTLs) and the underlying mechanism remains largely unknown. Here, we report the genetic mapping of three new QTLs, qLG2, qWG2, and qLG8 that each exerts a semi-dominant effect on grain shape in cultivated rice. These QTLs were validated using populations derived from the corresponding chromosome segment substitution lines (CSSLs), and were further delimited to small genomic intervals in progeny testing experiments. Especially, qLG2/qWG2 was placed into an about 250-kb genomic candidate region, and 14 predicted ORFs localized within the interval. We also evaluated the individual and pyramiding genetic effect(s) of these QTL(s) using the corresponding nearly isogenic lines, and found that they have additive effects on the traits. Collectively, these findings provided useful information as a tool to improve grain shape in crop breeding programs and established foundations for future QTL cloning.

Examining two sets of introgression lines across multiple environments reveals background-independent and stably expressed quantitative trait loci of fiber quality in cotton

Key messageBackground-independent (BI) and stably expressed (SE) quantitative trait loci (QTLs) were identified using two sets of introgression lines across multiple environments. Genetic background more greatly affected fiber quality traits than environmental factors. Sixty-one SE-QTLs, including two BI-QTLs, were novel and 48 SE-QTLs, including seven BI-QTLs, were previously reported.Cotton fiber quality traits are controlled by QTLs and are susceptible to environmental influence. Fiber quality improvement is an essential goal in cotton breeding but is hindered by limited knowledge of the genetic basis of fiber quality traits. In this study, two sets of introgression lines of Gossypium hirsutum × G. barbadense were used to dissect the QTL stability of three fiber quality traits (fiber length, strength and micronaire) across environments using 551 simple sequence repeat markers selected from our high-density genetic map. A total of 76 and 120 QTLs were detected in the CCRI36 and CCRI45 backgrounds, respectively. Nine BI-QTLs were found, and 78 (41.71%) of the detected QTLs were reported previously. Thirty-nine and 79 QTLs were SE-QTLs in at least two environments in the CCRI36 and CCRI45 backgrounds, respectively. Forty-eight SE-QTLs, including seven BI-QTLs, were confirmed in previous reports, and 61 SE-QTLs, including two BI-QTLs, were considered novel. These results indicate that genetic background more strongly impacts on fiber quality traits than environmental factors. Twenty-three clusters with BI- and/or SE-QTLs were identified, 19 of which harbored favorable alleles from G. barbadense for two or three fiber quality traits. This study is the first report using two sets of introgression lines to identify fiber quality QTLs across environments in cotton, providing insights into the effect of genetic backgrounds and environments on the QTL expression of fiber quality and important information for the genetic basis underlying fiber quality traits toward QTL cloning and molecular breeding.

Molecular mapping and identification of quantitative trait loci for domestication traits in the field cress (Lepidium campestre L.) genome

Lepidium campestre (L.) or field cress is a multifaceted oilseed plant, which is not yet domesticated. Moreover, the molecular and genetic mechanisms underlying the domestication traits of field cress remain largely elusive. The overarching goal of this study is to identify quantitative trait loci (QTL) that are fundamental for domestication of field cress. Mapping and dissecting quantitative trait variation may provide important insights into genomic trajectories underlying field cress domestication. We used 7624 single nucleotide polymorphism (SNP) markers for QTL mapping in 428 F2 interspecific hybrid individuals, while field phenotyping was conducted in F2:3 segregating families. We applied multiple QTL mapping algorithms to detect and estimate the QTL effects for seven important domestication traits of field cress. Verification of pod shattering across sites revealed that the non-shattering lines declined drastically whereas the shattering lines increased sharply, possibly due to inbreeding followed by selection events. In total, 1461 of the 7624 SNP loci were mapped to eight linkage groups (LGs), spanning 571.9 cM map length. We identified 27 QTL across all LGs of field cress genome, which captured medium to high heritability, implying that genomics-assisted selection could deliver domesticated lines in field cress breeding. The use of high throughput genotyping can accelerate the process of domestication in novel crop species. This is the first QTL mapping analysis in the field cress genome that may lay a foundational framework for positional or functional QTL cloning, introgression as well as genomics-assisted breeding in field cress domestication.

Construction and characterization of a BAC library for flue-cured tobacco line with high resistance to blank shank

<p indent="0mm">Tobacco (<italic>N. tabacum</italic>) is an important model crop in molecular biology research. In this study, a bacterial artificial chromosome (BAC) library of a flue-cured tobacco line 14–60 with high blank shank resistance and good quality was constructed. High molecular weight DNA was isolated using intact nuclei from tobacco, partially cleaved with <italic>Hin</italic>d III and cloned into the pIndigoBAC536-S vector. The BAC library consisted of 414,720 clones arrayed in one thousand and eighty 384-microtite plates, with an average insert size of 123 kb ranging from 97.0–145.5 kb. No empty insert clone was found. Based on an estimated genome size of 4500 Mb for common tobacco, the BAC library was estimated to cover 11 times of genome equivalents. The utility of the library was further confirmed by screening the library with the primers of tobacco <italic>hem</italic>A, <italic>NtFT</italic>, and<italic> eIF4E-</italic>1 genes. The high capacity library will serve as a giant genomic resource for map-based cloning of quantitative trait loci or genes associated with important agronomic and smoking quality traits or resistance to blank shank, physical mapping and comparative genome analysis.

Genome-Wide Identification of QTLs for Grain Protein Content Based on Genotyping-by-Resequencing and Verification of qGPC1-1 in Rice.

To clarify the genetic mechanism underlying grain protein content (GPC) and to improve rice grain qualities, the mapping and cloning of quantitative trait loci (QTLs) controlling the natural variation of GPC are very important. Based on genotyping-by-resequencing, a total of 14 QTLs were detected with the Huanghuazhan/Jizi1560 (HHZ/JZ1560) recombinant inbred line (RIL) population in 2016 and 2017. Seven of the fourteen QTLs were repeatedly identified across two years. Using three residual heterozygote-derived populations, a stably inherited QTL named as qGPC1-1 was validated and delimited to a ~862 kb marker interval JD1006–JD1075 on the short arm of chromosome 1. Comparing the GPC values of the RIL population determined by near infrared reflectance spectroscopy (NIRS) and Kjeldahl nitrogen determination (KND) methods, high correlation coefficients (0.966 and 0.983) were observed in 2016 and 2017. Furthermore, 12 of the 14 QTLs were identically identified with the GPC measured by the two methods. These results indicated that instead of the traditional KND method, the rapid and easy-to-operate NIRS was suitable for analyzing a massive number of samples in mapping and cloning QTLs for GPC. Using the gel-based low-density map consisted of 208 simple sequence repeat (SSR) and insert/deletion (InDel) markers, the same number of QTLs (fourteen) were identified in the same HHZ/JZ1560 RIL population, and three QTLs were repeatedly detected across two years. More stably expressed QTLs were identified based on the genome resequencing, which might be attributed to the high-density map, increasing the detection power of minor QTLs. Our results are helpful in dissecting the genetic basis of GPC and improving rice grain qualities through molecular assisted selection.

A genome-wide association study uncovers consistent quantitative trait loci for resistance to Verticillium wilt and Fusarium wilt race 4 in the US Upland cotton.

A high-resolution GWAS detected consistent QTL for resistance to Verticillium wilt and Fusarium wilt race 4 in 376 U.S. Upland cotton accessions based on six independent replicated greenhouse tests. Verticillium wilt (VW, caused by Verticillium dahliae Kleb.) and Fusarium wilt (FOV, caused by Fusarium oxysporum f.sp. vasinfectum Atk. Sny & Hans) are the most important soil-borne fungal diseases in cotton. To augment and refine resistance quantitative trait loci (QTL), we conducted a genome-wide association study (GWAS) using high-density genotyping with the CottonSNP63K array. Resistance of 376 US Upland cotton accessions to a defoliating VW and virulent FOV4 was evaluated in four and two independent replicated greenhouse tests, respectively. A total of 15 and 13 QTL for VW and FOV4 resistances were anchored by 30 (on five chromosomes) and 56 (on six chromosomes) significant single nucleotide polymorphic (SNPs) markers, respectively. QTL on c8, c10, c16, and c21 were consistent in two or more tests for VW resistance, while two QTL on c8 and c14 were consistent for FOV4 resistance in two tests. Two QTL clusters on c16 and c19 were observed for both VW and FOV4 resistance, suggesting that these genomic regions may harbor genes in response to both diseases. Using BLAST search against the sequenced TM-1 genome, 30 and 35 candidate genes were identified on four QTL for VW resistance and on three QTL for FOV4 resistance, respectively. These genomic regions were rich in NBS-LRR genes presented in clusters. The results create opportunities for further studies to determine the correlations of field resistance with these QTL, molecular examinations of VW and FOV4 resistances, marker-assisted selection (MAS) and eventual cloning of QTL for disease resistance in cotton.

Fine-mapping QTLs and the validation of candidate genes for Aluminum tolerance using a high-density genetic map

Aluminium (Al) stress is one of the most adverse abiotic factors limiting the growth and productivity of crops in acidic soils. Fine-mapping and cloning of quantitative trait loci (QTLs) provides an effective tool in analysing the genetic mechanisms underlying Al tolerance and in breeding Al-tolerant soybean varieties. Soybean cultivar Huachun2 in South China has been reported to be highly tolerant to multiple abiotic stresses in acidic soils, including Al stress. Here, we employ a recombinant inbred line (RIL) population derived from a cross of Huachun2 and Wayao to investigate the Al-tolerance QTLs. The prioritization method and qRT-PCR were applied to predict candidate genes in each QTL. Additionally, the functions of GmGSTU9 and GmPrx145 were investigated in transgenic soybean hairy roots. In total, five QTLs associated with relative root elongation and Al content were identified by using the high-density genetic map in hydroponics. GmGSTU9, which encodes a glutathione S-transferase gene in qAl06, and GmPrx145, which encodes a class III peroxidase gene in qAl-HC2, were selected to further study the gene functions by using transgenic soybean hairy roots. In transgenic soybean hairy roots, the MDA, H2O2 and O2− contents in GmGSTU9- and GmPrx145-overexpressing hairy roots were lower than those in the control and RNA-interference-exposed hairy roots under Al stress. GmGSTU9 and GmPrx145 detected in qAl06 and qAl-HC2, respectively, positively regulate Al tolerance in soybean hairy roots by improving the antioxidant activity. These Al tolerance genes and molecular markers will be useful for marker-assisted selection to improve the Al tolerance of soybeans in acidic soils.

Detection of QTLs associated with mungbean yellow mosaic virus (MYMV) resistance using the interspecific cross of Vigna radiata × Vigna umbellata.

Mungbean (Vigna radiata) and ricebean (V. umbellata) were utilized to obtain an inter-specific recombinant inbred line (RIL) population with the objective of detecting quantitative trait loci (QTL) associated with mungbean yellow mosaic virus (MYMV) resistance. To precisely map QTLs, accurate genetic linkage maps are essential. In the present study, genotyping-by-sequencing (GBS) platform was utilized to develop the genetic linkage map. The map contained 538 single nucleotide polymorphism (SNP) markers, consisted of 11 linkage groups and spanned for 1291.7cM with an average marker distance of 2.40cM. The individual linkage group ranged from 90.2 to 149.1cM in length, and the SNP markers were evenly distributed in the genetic linkage map, with 30-79 SNP markers per chromosome. The QTL analysis using the genetic map and 2years (2015 and 2016) of phenotyping data identified five QTLs with phenotypic variation explained (PVE) from 10.11 to 20.04%. Of these, a QTL on chromosome 4, designated as qMYMV4-1, was major and stably detected in the same marker interval in both years. This QTL region harbours possible candidate genes for controlling MYMV resistance. The linkage map and QTL/gene (s) for MYMV resistance identified in this study should be useful for QTL fine mapping and cloning for further studies.

Discovering consensus genomic regions in wheat for root-related traits by QTL meta-analysis

Root system architecture is crucial for wheat adaptation to drought stress, but phenotyping for root traits in breeding programmes is difficult and time-consuming owing to the belowground characteristics of the system. Identifying quantitative trait loci (QTLs) and linked molecular markers and using marker-assisted selection is an efficient way to increase selection efficiency and boost genetic gains in breeding programmes. Hundreds of QTLs have been identified for different root traits in the last few years. In the current study, consensus QTL regions were identified through QTL meta-analysis. First, a consensus map comprising 7352 markers was constructed. For the meta-analysis, 754 QTLs were retrieved from the literature and 634 of them were projected onto the consensus map. Meta-analysis grouped 557 QTLs in 94 consensus QTL regions, or meta-QTLs (MQTLs), and 18 QTLs remained as singletons. The recently published genome sequence of wheat was used to search for gene models within the MQTL peaks. As a result, gene models for 68 of the 94 Root_MQTLs were found, 35 of them related to root architecture and/or drought stress response. This work will facilitate QTL cloning and pyramiding to develop new cultivars with specific root architecture for coping with environmental constraints.

Dissecting the genetic basis of fiber quality and yield traits in interspecific backcross populations of Gossypium hirsutum\u2009\xd7\u2009Gossypium barbadense

Fiber quality and yield are important traits of cotton. Quantitative trait locus (QTL) mapping is a prerequisite for marker-assisted selection (MAS) in cotton breeding. To identify QTLs for fiber quality and yield traits, 4 backcross-generation populations (BC1F1, BC1S1, BC2F1, and BC3F0) were developed from an interspecific cross between CCRI36 (Gossypium hirsutum L.) and Hai1 (G. barbadense L.). A total of 153 QTLs for fiber quality and yield traits were identified based on data from the BC1F1, BC1S1, BC2F1 and BC3F0 populations in the field and from the BC2F1 population in an artificial disease nursery using a high-density genetic linkage map with 2292 marker loci covering 5115.16 centimorgans (cM) from the BC1F1 population. These QTLs were located on 24 chromosomes, and each could explain 4.98–19.80% of the observed phenotypic variations. Among the 153 QTLs, 30 were consistent with those identified previously. Specifically, 23 QTLs were stably detected in 2 or 3 environments or generations, 6 of which were consistent with those identified previously and the other 17 of which were stable and novel. Ten QTL clusters for different traits were found and 9 of them were novel, which explained the significant correlations among some phenotypic traits in the populations. The results including these stable or consensus QTLs provide valuable information for marker-assisted selection (MAS) in cotton breeding and will help better understand the genetic basis of fiber quality and yield traits, which can then be used in QTL cloning.

Identification and QTL mapping of Z550, a rice backcrossed inbred line with increased grains per panicle

An elite backcrossed inbred line Z550 with increased grains per panicle was identified from advanced backcrosses between Nipponbare and Xihui 18 by simple sequence repeat (SSR) marker-assisted selection (MAS). Z550 carries 13 substitution segments distributed on chromosomes 1, 6, 7, 8, 9, 10, and 12, with an average substitution length of 1.68 Mb. Compared with the Nipponbare parental line, plant height, panicle length, spikelets per panicle, grains per panicle, and grain weight for Z550 were significantly increased. While the grain width of Z550 was significantly narrower, and the seed setting ratio (81.43%) was significantly lower than that of Nipponbare, it is still sufficient for breeding purposes. Quantitative trait loci (QTLs) mapping for important agronomic traits was conducted with the F2 population derived from Nipponbare crossed with Z550 using the restricted maximum likelihood (REML) method. A total of 16, including 12 previously unreported QTLs were detected, with contribution rates ranging from 1.46 to 10.49%. Grains per panicle was controlled by 8 QTLs, 5 of which increased number of grains whereas 3 decreased it. qGPP-1, with the largest contribution (10.49%), was estimated to increase grains per panicle by 30.67, while qGPP-9, with the minimum contribution rate (2.47%), had an effect of increasing grains per panicle by 15.79. These results will be useful for further development of single segment substitution lines with major QTLs, and for research of their molecular functions via QTL cloning.

Consensus genetic linkage map construction and QTL mapping for plant height-related traits in linseed flax (Linum usitatissimum L.)

BackgroundFlax is an important field crop that can be used for either oilseed or fiber production. Plant height and technical length are important characters for flax. For linseed flax, plants usually have a short technical length and plant height than those for fiber flax. As an important agronomical character for fiber and linseed flax, plant height is usually a selection target for breeding. However, because of limited technologies and methods available, there has been little research focused on discovering the molecular mechanism controlling plant height.ResultsIn this study, two related recombinant inbred line (RIL) populations developed from crosses of linseed and fiber parents were developed and phenotyped for plant height and technical length in four environments. A consensus linkage map based on two RIL populations was constructed using SNP markers generated by genotyping by sequencing (GBS) technology. A total of 4497 single nucleotide polymorphism (SNP) markers were included on 15 linkage groups with an average marker density of one marker every 2.71 cM. Quantitative trait locus (QTL) mapping analysis was performed for plant height and technical length using the two populations. A total of 19 QTLs were identified for plant height and technical length. For the MH population, eight plant height QTLs and seven technical length QTLs were identified, five of which were common QTLs for both traits. For the PH population, six plant height and three technical length QTLs were identified. By comparing the QTLs and candidate gene information in the two population, two common QTLs and three candidate genes were discovered.ConclusionsThis study provides a foundation for map-based cloning of QTLs and marker-assisted selection for plant height-related traits in linseed and fiber flax.