Cloning Of Quantitative Trait Loci Research Articles

Mapping and cloning of quantitative trait loci for phosphorus efficiency in crops: opportunities and challenges

Phosphorus (P) is an essential mineral element required in large quantities by plants. Globally, the availability of P in many soils is poor. Breeding crops that can acquire and utilise this limited resource with high efficiency is an important goal for agricultural sustainability in the future. The mapping and cloning of quantitative trait loci (QTLs) provides an effective tool in analyzing the genetic mechanisms underlying P efficiency and breeding P-efficient varieties. This paper describes the QTL mapping of traits related to P efficiency which impact on shoot biomass or yield of crops in the past 20 years. It summarises the progress of studies on crop P-efficiency related QTLs and discusses the challenges for the cloning of QTLs. It proposes a scheme to develop crop genotypes with improved P efficiency. It also describes emerging methods, such as QTL-seq, genome-wide association analysis, and RNA-seq, that aid the rapid identification of P-efficiency related genes in crops. Traits conferring P efficiency are heritable. Thus, it is feasible to incorporate phenotyping and selection for P efficiency in crop breeding programs. Identification of QTLs for target traits is a key step to enhancing the P efficiency of crops. Numerous QTLs have been identified that affect P efficiency in key crops, but few causal genes have been identified and breeding P-efficient crop varieties using marker-assisted selection (MAS) has not progressed far. The challenge now is to identify the specific genes controlling P-efficiency related traits. The availability of complete genome sequences for more crops, and the combination of conventional linkage mapping, association mapping, QTL-seq, transcriptomics and gene editing technologies can accelerate the cloning and confirmation of genes underlying QTL affecting P-efficiency related traits. Knowledge of these genes will be helpful in revealing the molecular mechanisms underlying P efficiency in crops, as well as providing the opportunity to improve crop P efficiency through MAS or gene manipulation.

Mapping QTLs for cold tolerance at seedling stage using an Oryza sativa × O. rufipogon backcross inbred line population

Tolerance to low temperature is an important factor affecting the growth and development of rice (Oryza sativa L.) at an early growing season in the temperate region, and at high altitudes of tropical regions. In this study, a backcross inbred line (BIL) population derived from an interspecific cross between Xieqingzao B (O. sativa L.) and an accession of Dongxiang wild rice (O. rufipogon Griff.) was used to identify quantitative trait loci (QTLs) associated with cold tolerance at the seedling stage. Seedlings were treated with a temperature of 6°C for 2 days and seedling mortality was measured for QTL mapping. QTL analysis was performed on the whole BIL population and on one subpopulation that showed Xieqingzao B homozygous at QTL detected in the whole population. One major QTL, qSCT8, and one QTL, qSCT4.3, with smaller effect was found in the whole population. The QTLs qSCT8 and qSCT4.3 were mapped on chromosome 8 and 4, explaining 60.96% and 8.83% of the phenotypic variance, respectively. In the subpopulation, three QTLs, qSCT4.1, qSCT4.2 and qSCT12, accounting for 56.22%, 57.62% and 53.09% of the phenotypic variance, respectively, were detected on chromosome 4 and 12. At all five loci, the alleles introduced from the Dongxiang wild rice were effective in decreasing seedling mortality. Our results provide a basis for fine mapping and cloning of QTLs associated with cold tolerance, and the markers linked with QTLs could be used to improve the cold tolerance of rice varieties by marker-assisted selection.

Construction and characterization of a bacterial artificial chromosome library for Gossypium mustelinum.

A bacterial artificial chromosome (BAC) library for G. mustelinum Miers ex G. Watt (AD4) was constructed. Intact nuclei from G. mustelinum (AD4) were used to isolate high molecular weight DNA, which was partially cleaved with Hind III and cloned into pSMART BAC (Hind III) vectors. The BAC library consisted of 208,182 clones arrayed in 542 384-microtiter plates, with an average insert size of 121.72 kb ranging from 100 to 150 kb. About 2% of the clones did not contain inserts. Based on an estimated genome size of 2372 Mb for G. mustelinum, the BAC library was estimated to have a total coverage of 10.50 × genome equivalents. The high capacity library of G. mustelinum will serve as a giant gene resource for map-based cloning of quantitative trait loci or genes associated with important agronomic traits or resistance to Verticillium wilt, physical mapping and comparative genome analysis.

Intraspecific variation of residual heterozygosity and its utility for quantitative genetic studies in maize

BackgroundResidual heterozygosity (RH) in advanced inbred lines of plants benefits quantitative trait locus (QTL) mapping studies. However, knowledge of factors affecting the genome-wide distribution of RH remains limited.ResultsA set of 2196 heterogeneous inbred family (HIF) maize lines derived from 12 recombinant inbred line (RIL) populations was genotyped using the Maize50K SNP chip. A total of 18,615 unique RH intervals were identified, ranging from 505 to 2095 intervals per population, with average maize genome coverage of 94.8%. Across all populations, there were 8.6 RH intervals per HIF line on average, ranging from 1.8 to 14 intervals; the average size of an RH interval was approximately 58.7 Mb, ranging from 7.2 to 74.1 Mb. A given RH region was present in an average of 5 different individuals within a population. Seven RH hotspots, where RH segments were enriched in the genome, were found to be subject to selection during population development. The RH patterns varied significantly across populations, presumably reflecting differences in the genetic background of each population, and 8 QTLs were found to affect heterozygosity levels in the RH hotspots. The potential use of this HIF library for the fine mapping of QTLs was assessed based on publicly available QTL information, achieving a ≤ 1 Mb resolution on average.ConclusionThe examined library of HIF lines offers insight into the RH landscape and its intraspecific variation and provides a useful resource for the QTL cloning of important agronomic traits in maize.

Identification and Fine-Mapping of a Major Maize Leaf Width QTL in a Re-sequenced Large Recombinant Inbred Lines Population.

Leaf width (LW) influences canopy architecture of population-cultured maize and can thus contribute to density breeding. In previous studies, almost all maize LW-related mutants have extreme effect on leaf development or accompanied unfavorable phenotypes. In addition, the identification of quantitative trait loci (QTLs) has been resolution-limited, with cloning and fine-mapping rarely performed. Here, we constructed a bin map for 670 recombinant inbred lines (RILs) using ∼1.2 billion 100-bp re-sequencing reads. QTL analysis of the LW trait directly narrowed the major effect QTL, qLW4, to a ∼270-kb interval. A fine-mapping population and near-isogenic lines (NILs) were quickly constructed using a key RIL harboring heterozygous genotypes across the qLW4 region. A recombinant-derived progeny testing strategy was subsequently used to further fine-map qLW4 to a 55-kb interval. Examination of NILs revealed that qLW4 has a completely dominant effect on LW, with no additional effect on leaf length. Candidate gene analysis suggested that this locus may be a novel LW controlling allele in maize. Our findings demonstrate the advantage of large-population high-density bin mapping, and suggest a strategy for efficiently fine-mapping or even cloning of QTLs. These results should also be helpful for further dissection of the genetic mechanism of LW variation, and benefit maize density breeding.

Identification of QTL for Fiber Quality and Yield Traits Using Two Immortalized Backcross Populations in Upland Cotton.

Two immortalized backcross populations (DHBCF1s and JMBCF1s) were developed using a recombinant inbred line (RIL) population crossed with the two parents DH962 and Jimian5 (as the males), respectively. The fiber quality and yield component traits of the two backcross populations were phenotyped at four environments (two locations, two years). One hundred seventy-eight quantitative trait loci (QTL) were detected including 76 for fiber qualities and 102 for yield components, explaining 4.08–17.79% of the phenotypic variation (PV). Among the 178 QTL, 22 stable QTL were detected in more than one environment or population. A stable QTL, qFL-c10-1, was detected in the previous F2 population, a RIL population in 3 environments and the current two BCF1 populations in this study, explaining 5.79–37.09% of the PV. Additionally, 117 and 110 main-effect QTL (M-QTL) and 47 and 191 digenic epistatic QTL (E-QTL) were detected in the DHBCF1s and JMBCF1s populations, respectively. The effect of digenic epistasis played a more important role on lint percentage, fiber length and fiber strength. These results obtained in the present study provided more resources to obtain stable QTL, confirming the authenticity and reliability of the QTL for molecular marker-assisted selection breeding and QTL cloning.

Genetic control of flowering time in rice: integration of Mendelian genetics and genomics.

Integration of previous Mendelian genetic analyses and recent molecular genomics approaches, such as linkage mapping and QTL cloning, dramatically strengthened our current understanding of genetic control of rice flowering time. Flowering time is one of the most important agronomic traits for seed production in rice (Oryza sativa L.). It is controlled mainly by genes associated with photoperiod sensitivity, particularly in short-day plants such as rice. Since the early twentieth century, rice breeders and researchers have been interested in elucidating the genetic basis of flowering time because its modification is important for regional adaptation and yield optimization. Although flowering time is a complex trait controlled by many quantitative trait loci (QTLs), classical genetic studies have shown that many associated genes are inherited in accordance with Mendelian laws. Decoding the rice genome sequence opened a new era in understanding the genetic control of flowering time on the basis of genome-wide mapping and gene cloning. Heading date 1 (Hd1) was the first flowering time QTL to be isolated using natural variation in rice. Recent accumulation of information on rice genome has facilitated the cloning of other QTLs, including those with minor effects on flowering time. This information has allowed us to rediscover some of the flowering genes that were identified by classical Mendelian genetics. The genes characterized so far, including Hd1, have been assigned to specific photoperiod pathways. In this review, we provide an overview of the studies that led to an in-depth understanding of the genetic control of flowering time in rice, and of the current state of improving and fine-tuning this trait for rice breeding.

Smart Engineering of Genetic Resources for Enhanced Salinity Tolerance in Crop Plants

ABSTRACTSalinity is a consistent factor of crop productivity loss in the world and in particular arid and semi-arid areas where the soil salinity and saline water are major problems. Plants employ various mechanisms to cope with salinity stress and activate an array of stress-responsive genes to counteract the salinity-induced osmotic and ionic stresses. Genetic improvement for salinity tolerance is challenging, and thus progress attained over the several decades has been far less than anticipated. The generation of an explosion of knowledge and technology related to genetics and genomics over the last few decades is promising in providing powerful tools for future development of salinity-tolerant cultivars. Despite a major progress in defining the underlying mechanisms of salinity tolerance, there are still major challenges to be overcome in translating and integrating the resultant information at the molecular level into plant-breeding practices. Various approaches have been suggested to improve the efficiency of plant breeding for increasing plant productivity under saline environments. In this context, breeding for salinity tolerance in crops largely depends upon the availability of genetic resources of tolerance, reliable screening techniques, identification of genetic components of tolerance, and successful genetic manipulation of desired genetic backgrounds. The efficiency of selection and breeding in the stressful environments can be improved through marker-assisted selection. To date, this is almost exclusively applied to major genes, but this requires to be extended to quantitative trait loci (QTLs) controlling complex traits such as salinity tolerance to greatly enhance the impact. Moreover, methodologies for high-throughput genotyping, and the development of an array of “functional” markers can be much supportive. The introduction of novel genes or alteration in the expression patterns of the existing genes through the generation of transgenic plants can also be employed to overcome the limits in classical plant breeding. The introgression of wild halophytic attribute genes facilitated by genetic engineering is an alternative approach to bypass interspecific hybridization barriers, which will stimulate breakthrough in the future agriculture. The molecular dissection of salinity-tolerance trait, accompanying the classical quantitative genetics, is a substantial progress in updating tools and methods for the manipulation of plant genomes. Methods of gene discovery such as identification of candidate genes, QTL cloning, linkage and association mapping, and functional genomics such as identification of transcripts and proteins involved in salinity tolerance are necessary to manipulate the molecular mechanisms underlying the complex phenotype of salinity tolerance. Some of the challenges and opportunities have also been addressed in the present review with a particular emphasis on molecular breeding approaches to be employed in combination with other crop improvement strategies to develop salinity-tolerant cultivars.

Dissecting the Genetic Architecture of Leaf Rust Resistance in Wheat by QTL Meta-Analysis.

Leaf rust is an important disease that causes significant yield losses in wheat. Many studies have reported the identification of quantitative trait loci (QTL) controlling leaf rust resistance; therefore, QTL meta-analysis has become a useful tool for identifying consensus QTL and refining QTL positions among them. In this study, QTL meta-analysis was conducted using reported results on the number, position, and effects of QTL for leaf rust resistance in bread and durum wheat. Investigation of 14 leaf rust resistance traits from 19 studies involving 20 mapping populations and 33 different parental lines provided information for 144 unique QTL that were projected onto the Wheat Composite 2004 reference map. In total, 35 meta-QTL for leaf rust resistance traits were identified in 17 wheat chromosomes and 13 QTL remained as unique QTL. The results will facilitate further work on the cloning of QTL for pyramiding minor- and partial-effect resistance genes to develop varieties with durable resistance to leaf rust.

Construction of the High-Density Genetic Linkage Map and Chromosome Map of Large Yellow Croaker (Larimichthys crocea).

High-density genetic maps are essential for genome assembly, comparative genomic analysis and fine mapping of complex traits. In this study, 31,191 single nucleotide polymorphisms (SNPs) evenly distributed across the large yellow croaker (Larimichthys crocea) genome were identified using restriction-site associated DNA sequencing (RAD-seq). Among them, 10,150 high-confidence SNPs were assigned to 24 consensus linkage groups (LGs). The total length of the genetic linkage map was 5451.3 cM with an average distance of 0.54 cM between loci. This represents the densest genetic map currently reported for large yellow croaker. Using 2889 SNPs to target specific scaffolds, we assigned 533 scaffolds, comprising 421.44 Mb (62.04%) of the large yellow croaker assembled sequence, to the 24 linkage groups. The mapped assembly scaffolds in large yellow croaker were used for genome synteny analyses against the stickleback (Gasterosteus aculeatus) and medaka (Oryzias latipes). Greater synteny was observed between large yellow croaker and stickleback. This supports the hypothesis that large yellow croaker is more closely related to stickleback than to medaka. Moreover, 1274 immunity-related genes and 195 hypoxia-related genes were mapped to the 24 chromosomes of large yellow croaker. The integration of the high-resolution genetic map and the assembled sequence provides a valuable resource for fine mapping and positional cloning of quantitative trait loci associated with economically important traits in large yellow croaker.

Validation of QTL for resistance to Aphanomyces euteiches in different pea genetic backgrounds using near-isogenic lines.

Marker-assisted backcrossing was used to generate pea NILs carrying individual or combined resistance alleles at main Aphanomyces resistance QTL. The effects of several QTL were successfully validated depending on genetic backgrounds. Quantitative trait loci (QTL) validation is an important and often overlooked step before subsequent research in QTL cloning or marker-assisted breeding for disease resistance in plants. Validation of QTL controlling partial resistance to Aphanomyces root rot, one of the most damaging diseases of pea worldwide, is of major interest for the future development of resistant varieties. The aim of this study was to validate, in different genetic backgrounds, the effects of various resistance alleles at seven main resistance QTL recently identified. Five backcross-assisted selection programs were developed. In each, resistance alleles at one to three of the seven main Aphanomyces resistance QTL were transferred into three genetic backgrounds, including two agronomically important spring (Eden) and winter (Isard) pea cultivars. The subsequent near-isogenic lines (NILs) were evaluated for resistance to two reference strains of the main A. euteiches pathotypes under controlled conditions. The NILs carrying resistance alleles at the major-effect QTL Ae-Ps4.5 and Ae-Ps7.6, either individually or in combination with resistance alleles at other QTL, showed significantly reduced disease severity compared to NILs without resistance alleles. Resistance alleles at some minor-effect QTL, especially Ae-Ps2.2 and Ae-Ps5.1, were also validated for their individual or combined effects on resistance. QTL×genetic background interactions were observed, mainly for QTL Ae-Ps7.6, the effect of which increased in the winter cultivar Isard. The pea NILs are a novel and valuable resource for further understanding the mechanisms underlying QTL and their integration in breeding programs.

Molecular Mapping of Restriction-Site Associated DNA Markers In Allotetraploid Upland Cotton.

Upland cotton (Gossypium hirsutum L., 2n = 52, AADD) is an allotetraploid, therefore the discovery of single nucleotide polymorphism (SNP) markers is difficult. The recent emergence of genome complexity reduction technologies based on the next-generation sequencing (NGS) platform has greatly expedited SNP discovery in crops with highly repetitive and complex genomes. Here we applied restriction-site associated DNA (RAD) sequencing technology for de novo SNP discovery in allotetraploid cotton. We identified 21,109 SNPs between the two parents and used these for genotyping of 161 recombinant inbred lines (RILs). Finally, a high dense linkage map comprising 4,153 loci over 3500-cM was developed based on the previous result. Using this map quantitative trait locus (QTLs) conferring fiber strength and Verticillium Wilt (VW) resistance were mapped to a more accurate region in comparison to the 1576-cM interval determined using the simple sequence repeat (SSR) genetic map. This suggests that the newly constructed map has more power and resolution than the previous SSR map. It will pave the way for the rapid identification of the marker-assisted selection in cotton breeding and cloning of QTL of interest traits.

Quantitative trait locus analysis of agronomic and quality-related traits in cultivated peanut (Arachis hypogaea L.).

Key message SSR-based QTL mapping provides useful information for map-based cloning of major QTLs and can be used to improve the agronomic and quality traits in cultivated peanut by marker-assisted selection. Cultivated peanut (Arachis hypogaea L.) is an allotetraploid species (AABB, 2n = 4× = 40), valued for its edible oil and digestible protein. Linkage mapping has been successfully conducted for most crops, and it has been applied to detect the quantitative trait loci (QTLs) of biotic and abiotic traits in peanut. However, the genetic basis of agronomic and quality-related traits remains unclear. In this study, high levels of phenotypic variation, broad-sense heritability and significant correlations were observed for agronomic and quality-related traits in an F 2:3 population. A genetic linkage map was constructed for cultivated peanut containing 470 simple sequence repeat (SSR) loci, with a total length of 1877.3 cM and average distance of 4.0 cM between flanking markers. For 10 agronomic traits, 24 QTLs were identified and each QTL explained 1.69–18.70 % of the phenotypic variance. For 8 quality-related traits, 12 QTLs were identified that explained 1.72–20.20 % of the phenotypic variance. Several QTLs for multiple traits were overlapped, reflecting the phenotypic correlation between these traits. The majority of QTLs exhibited obvious dominance or over-dominance effects on agronomic and quality traits, highlighting the importance of heterosis for breeding. A comparative analysis revealed genomic duplication and arrangement of peanut genome, which aids the assembly of scaffolds in genomic sequencing of Arachis hypogaea. Our QTL analysis results enabled us to clearly understand the genetic base of agronomic and quality traits in cultivated peanut, further accelerating the progress of map-based cloning of major QTLs and marker-assisted selection in future breeding.Electronic supplementary materialThe online version of this article (doi:10.1007/s00122-015-2493-1) contains supplementary material, which is available to authorized users.

Genetic analysis of flag leaf size and candidate genes determination of a major QTL for flag leaf width in rice.

BackgroundFlag leaf is the most essential organ for photosynthesis in rice and its size plays an important role in rice breeding for ideal plant-type. Flag leaf size affect photosynthesis to a certain extent, thereby influencing rice production. Several genes controlling leaf size and shape have been identified with mutants. Although a number of quantitative trait loci (QTLs) for leaf size and shape have been detected on 12 chromosomes with different populations of rice, few of them were cloned.ResultsThe pair-wise correlation analysis was conducted on length, width and length-width ratio of the flag leaf, and yield per plant in the core recombinant inbred lines of Liang-You-Pei-Jiu (LYP9) developed in Hainan and Hangzhou. There were significant correlations among the three flag leaf size and shape traits. Interestingly, a positive correlation was found between flag leaf width and yield per plant. Based on the high-resolution linkage map we constructed before, 43 QTLs were detected for three flag leaf size and shape traits and yield per plant, among which 31 QTLs were unreported so far. Seven QTLs were identified common in two environments. And qFLW7.2, a new major QTL for flag leaf width, was fine mapped within 27.1 kb region on chromosome 7. Both qFLW7.2 and qPY7 were located in the interval of 45.30 ~ 53.34 cM on chromosome 7, which coincided with the relationship between yield per plant (PY) and flag leaf width (FLW).ConclusionqFLW7.2, which explained 14% of the phenotypic variation, increased flag leaf width with 93–11 allele. Two candidate genes were selected based on sequence variation and expression difference between two parents, which facilitated further QTL cloning and molecular breeding in super rice.

Mapping QTLs related to rice seed storability under natural and artificial aging storage conditions

Seed aging or deterioration in rice (Oryza sativa L.) is a major problem for agronomic production and germplasm preservation. Deciphering the genetic mechanism involved in seed aging and improving seed storability is therefore a vital goal for rice breeding. A set of 85 backcross inbred lines derived from the backcross ‘Sasanishiki’ (japonica cv.)/‘Habataki’ (an indica cv. with strong seed storability)//‘Sasanishiki’ was used here to detect quantitative trait locus (QTL) controlling seed storability. Seeds were treated under natural (conventional storage for 48 months) and artificial aging storage conditions (i.e. increased temperature and relative humidity) and germination rate was used to evaluate seed storability. A total of thirteen QTLs for seed storability were identified on chromosomes 1, 2, 3, 4, 5, 7, 11 and 12, respectively. Among them, two QTLs, viz. qSSh-2-1 and qSSh-2-2, were repeatedly detected in both treatment conditions. In contrast, four (qSSh-4, qSSs-5-1, qSSs-5-2 and qSSh-12) and seven QTLs (qSSh-1, qSSh-3-1, qSSh-3-2, qSSh-3-3, qSSh-7-1, qSSh-7-2 and qSSh-11) were detected only once in natural and artificial aging treatments, respectively. The ‘Habataki’-derived alleles were observed to increase seed storability at all the loci except qSSs-5-1 and qSSs-5-2. The existence of QTLs qSSh-1, qSSh-3-1, qSSh-3-2, qSSh-3-3, qSSh-4, qSSh-7-1, qSSh-7-2 and qSSh-11 was confirmed using Habataki chromosome segment substitution lines in a Sasanishiki genetic background. These results provide an opportunity for map-based cloning of major QTLs for seed storability, thereby gaining an understanding of seed storability in rice and possibilities for its improvement.

A new genetic and deletion map of wheat chromosome 5A to detect candidate genes for quantitative traits

In the present study, a detailed deletion map for wheat chromosomes 5A and 5B is reported, as well as an integrated genetic linkage map of chromosome 5A enriched with single nucleotide polymorphism (SNP) markers, useful both for comparison studies with other existing maps and for mapping major genes and quantitative trait loci (QTLs). Physical mapping of 5,011 SNP markers was obtained using Chinese Spring bin deletion lines for the homoeologous chromosomes of group 5; 509 SNPs were also genetically mapped in a recombinant inbred line population segregating for chromosome 5A only, obtained by crossing the cultivar Chinese Spring and the disomic substitution line Chinese Spring-5A dicoccoides. The whole 5A genetic map, containing 572 markers, covered a total length of 248.7 cM distributed among three linkage groups of 83.5, 117.8 and 47.4, respectively. The majority of SNP markers physically mapped on 5A were mapped to a unique bin, while a small percentage was assigned a double location, suggesting the presence of a segment of 5A short arm which may have undergone a duplication followed by an insertion into the long arm of the same chromosome. A QTL analysis for yield components was performed, identifying a major QTL in the sub-telomeric region of chromosome 5A, corresponding to the 5AL15-0.67-0.78 bin; the chromosome segment was 23.5 cM long and included 111 markers. Candidate genes for yield components on chromosome 5A were identified through a syntenic genomic approach by comparison with genomes of model species. Putative function analysis revealed genes involved in basic metabolism and in stress condition responses, including heat shock proteins, chaperones, serine/threonine protein kinases and membrane transporters, located in the region of the QTL. This information represents an important step for map-based and candidate gene-based cloning of yield QTLs.

Comparative mapping of chalkiness components in rice using five populations across two environments.

BackgroundChalkiness is a major constraint in rice production because it is one of the key factors determining grain quality (appearance, processing, milling, storing, eating, and cooking quality) and price. Its reduction is a major goal, and the primary purpose of this study was to dissect the genetic basis of grain chalkiness. Using five populations across two environments, we also sought to determine how many quantitative trait loci (QTL) can be consistently detected. We obtained an integrated genetic map using the data from five mapping populations and further confirmed the reliability of the identified QTL.ResultsA total of 79 QTL associated with six chalkiness traits (chalkiness rate, white core rate, white belly rate, chalkiness area, white core area, and white belly area) were mapped on 12 chromosomes using five populations (two doubled haploid lines and three recombinant inbred lines) across two environments (Hainan in 2004 and Wuhan in 2004). The final integrated map included 430 markers; 58.3% of the QTL clustered together (QTL clusters), 71.4% of the QTL clusters were identified in two or more populations, and 36.1% of the QTL were consistently detected in the two environments. The QTL could be detected again and showed dominance (qWBR1, qWBR8, qWBR12, and qCR5) or overdominance effects (qWCR7) for the rate of the white belly or white core, respectively, and all four QTL clusters derived from Zhenshan 97 controlling white belly rate were stably and reliably identified in an F2 population.ConclusionsOur results identified 79 QTL associated with six chalkiness traits using five populations across two environments and yielded an integrated genetic map, indicating most of the QTL clustered together and could be detected in different backgrounds. The identified QTL were stable and reliable in the F2 population, and they may facilitate our understanding of the QTL related to chalkiness traits in different populations and various environments, the relationships among the various chalkiness QTL, and the genetic basis for chalkiness. Thus, our results may be immediately used for map-based cloning of important QTL and in marker-assisted breeding to improve grain quality in rice breeding.

A ddRAD-based genetic map and its integration with the genome assembly of Japanese eel (Anguilla japonica) provides insights into genome evolution after the teleost-specific genome duplication

BackgroundRecent advancements in next-generation sequencing technology have enabled cost-effective sequencing of whole or partial genomes, permitting the discovery and characterization of molecular polymorphisms. Double-digest restriction-site associated DNA sequencing (ddRAD-seq) is a powerful and inexpensive approach to developing numerous single nucleotide polymorphism (SNP) markers and constructing a high-density genetic map. To enrich genomic resources for Japanese eel (Anguilla japonica), we constructed a ddRAD-based genetic map using an Ion Torrent Personal Genome Machine and anchored scaffolds of the current genome assembly to 19 linkage groups of the Japanese eel. Furthermore, we compared the Japanese eel genome with genomes of model fishes to infer the history of genome evolution after the teleost-specific genome duplication.ResultsWe generated the ddRAD-based linkage map of the Japanese eel, where the maps for female and male spanned 1748.8 cM and 1294.5 cM, respectively, and were arranged into 19 linkage groups. A total of 2,672 SNP markers and 115 Simple Sequence Repeat markers provide anchor points to 1,252 scaffolds covering 151 Mb (13%) of the current genome assembly of the Japanese eel. Comparisons among the Japanese eel, medaka, zebrafish and spotted gar genomes showed highly conserved synteny among teleosts and revealed part of the eight major chromosomal rearrangement events that occurred soon after the teleost-specific genome duplication.ConclusionsThe ddRAD-seq approach combined with the Ion Torrent Personal Genome Machine sequencing allowed us to conduct efficient and flexible SNP genotyping. The integration of the genetic map and the assembled sequence provides a valuable resource for fine mapping and positional cloning of quantitative trait loci associated with economically important traits and for investigating comparative genomics of the Japanese eel.

Genetic Analysis of Grain Shape for Paddy and Brown Rice Using Introgression Lines

ABSTRACTGrain shape–related traits are important components determining rice (Oryza sativa L.) grain yield, and they are controlled by quantitative trait loci (QTL). To study the genetic basis of grain shape–related traits, we performed an experiment using a population of rice introgression lines (ILs) in two different environments. The results revealed that the 10 traits investigated were affected by 84 QTL that individually explained 5.04 to 66.26% of the phenotypic variation. Most of these QTL explained a modest proportion of the phenotypic variance, confirming that grain shape was inherited polygenically. Meanwhile, 75 of all the 84 QTL showed a pleiotropic effect or linkage association as a cause of these observed phenotypic correlations between the grain shape traits. Among the regions showing pleiotropic effect or linkage association, 71.4% were associated with both paddy and brown grain shape traits, which suggested that paddy and brown grain shape might be controlled by the same genes. Furthermore, 13 major stable QTL were detected in both environments, which offers an opportunity for marker‐aided improvement of rice grain shape quality and QTL cloning. The introgression lines harboring the 13 major stable QTL also represent a useful genetic resource for rice yield improvement via a design‐breeding approach in the future.

Increasing the density of markers around a major QTL controlling resistance to angular leaf spot in common bean

Angular leaf spot (ALS) causes major yield losses in the common bean (Phaseolus vulgaris L.), an important protein source in the human diet. This study describes the saturation around a major quantitative trait locus (QTL) region, ALS10.1, controlling resistance to ALS located on linkage group Pv10 and explores the genomic context of this region using available data from the P. vulgaris genome sequence. DArT-derived markers (STS-DArT) selected by bulk segregant analysis and SCAR and SSR markers were used to increase the resolution of the QTL, reducing the confidence interval of ALS10.1 from 13.4 to 3.0cM. The position of the SSR ATA220 coincided with the maximum LOD score of the QTL. Moreover, a new QTL (ALS10.2(UC)) was identified at the end of the same linkage group. Sequence analysis using the P. vulgaris genome located ten SSRs and seven STS-DArT on chromosome 10 (Pv10). Coincident linkage and genome positions of five markers enabled the definition of a core region for ALS10.1 spanning 5.3Mb. These markers are linked to putative genes related to disease resistance such as glycosyl transferase, ankyrin repeat-containing, phospholipase, and squamosa-promoter binding protein. Synteny analysis between ALS10.1 markers and the genome of soybean suggested a dynamic evolution of this locus in the common bean. The present study resulted in the identification of new candidate genes and markers closely linked to a major ALS disease resistance QTL, which can be used in marker-assisted selection, fine mapping and positional QTL cloning.