Quantitative trait locus (QTL) analysis is a powerful approach for identifying variants associated with the phenotypic variation of complex traits. However, selecting optimal methods and pre-processing steps require considerable time and effort. In this study, we demonstrated applicability and replicability of machine learning (ML) models in QTL analysis by evaluating their performance in comparison with conventional QTL analysis methods using 142 recombinant inbred lines derived from two
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Rice domestication has led to cultivated rice with no or short awns. Discovery of novel genes associated to awn length is of paramount importance for understanding the molecular mechanisms for the transformation of wild rice long awns to awnless cultivated rice. In this study, we employed Next-Generation Sequencing based QTL-seq approach to identify genomic regions associated with awn length using mapping population derived from a cross between awnless Tun Sart and awned Sobaekmangsudo. QTL-seq analysis identified two awn length QTLs viz.
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Understanding the genetics underlying heading date and yield-related traits is essential in wheat breeding for maximizing productivity under different environments. Using doubled haploid lines derived from two Korean wheat cultivars, we identified seven stable quantitative trait loci (QTLs) for yield-related traits, i.e., days to heading date (
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Cold stress is one of the serious abiotic stresses for stable rice production especially in high-latitude temperate region and high-altitude tropical area. Improving cold tolerance at seedling stage led stable seedling growth with yield stability. In this study, QTLs for cold tolerance at seedling stage were identified using the 96 introgression lines (ILs) derived from an inter-specific cross between Hwaseong (
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A total of 857 rice breed lines were used to evaluate rice blast resistance. Frequency of leaf spot index was skewed to the right of the 1-9 scale in bar plot, with a score of 7 showing the highest frequency. The average spot index score of 857 breed lines was 5.33. Associations showing higher than the threshold of ‒log10(P) = 5.17 were detected as significant associations. Significantly associated single nucleotide polymorphism (SNP) markers located within ± 250 kb on the lead SNP position was designated to one QTL locus of lead SNP markers. Five association loci were detected. Two associated QTLs detected on Chr. 4 were designated as qRB4.1 and qRB422, explaining 17.8% and 14.3% of total phenotypic variations, respectively. Associated QTLs detected on Chr. 1, 11, and 12 (one each) designated as qRB1, qRB11 and qRB12 explained 44.6%, 9.09%, and 13.7% of total phenotypic variations, respectively. We compared previously reported QTLs. The location of qRB4.2 was overlapped with the previously reported QTL for blast field resistance. The location of qRB12 was also overlapped with the field resistance leaf blast. The other one, qRB4.1, was overlapped with bacterial blight resistance.
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Rice culm is an important trait for determining rice lodging yield, and stem diameter has been suggested as a yield-related trait; however, studies for the genetic basis of its phenotypic variation are still required. In this study, we used 160 recombination inbred lines derived from a cross of two different rice varieties [‘Milyang23’ (Tongil rice) and ‘Giho’ (
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Pre-harvest sprouting (PHS) is one of the important traits that not only cause serious economic issues but also lead to reduction in grain quality and yield in rice (
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High-throughput genotyping has substantially advanced the quality and accuracy of single nucleotide polymorphism (SNP) discovery and provided an effective way to interpret phenotypic variations in a mapping population. High-resolution quantitative trait locus (QTL) mapping is important for understanding agricultural traits. However, constructing a high-resolution map without sufficient markers to detect QTLs/genes of agronomically important traits is laborious and time consuming. In this study, 160 recom-binant inbred lines (RILs) derived from a cross between Milyang23 and Gihobyeo were re-sequenced, and their SNPs were used for high-resolution QTL mapping of yield-related traits. A total of 1,850,671 high-quality SNPs from RILs were detected, and 3,563 bins were used as genetic markers to construct a high-resolution genetic map using the sliding window approach. The total genetic distance was 1,278.62 cM. Using the QTL analysis, we identified 35 QTLs controlling six yield traits, namely, culm length, panicle length, panicle number per plant, primary branch number per panicle, grain number per plant, and 100-grain weight. In addition, we detected major QTLs associated with culm length and grain number, and compared their physical distances using a conventional genetic map. These results showed that rapid, high-resolution QTL mapping using high-quality SNPs as bin markers is a powerful tool for fine-mapping and cloning important QTLs/genes.
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The production of chili pepper (
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Biofortification is a cost-effective method for increasing the availability of micronutrients. Rice breeding for high levels of micronutrients is one of the best approaches to solve the problem of malnutrition. In this study, we developed a doubled haploid (DH) population derived from a cross between the rice cultivars 93-11 and Milyang 352 and evaluated QTLs for grain micronutrients and grain shape. Two co-localized QTLs,
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The yield related traits are controlled by multiple quantitative trait loci (QTLs) and influenced by environmental change in rice. We analyzed QTLs for 15 yield related traits using two backcross populations, derived from crosses between IR64 as recurrent parent and Koshihikari as donor parent, through two years. A total of 67 backcross inbred lines (BILs) and 40 chromosome segment substitution lines (CSSLs) were genotyped using 183 SNP markers using a high-throughput genotyping system. Some genomic gaps between markers were identified in two populations. For fifteen traits in this study, 36 major QTLs (mQTLs) for 12 traits and 16 digenic epistatic QTLs (EpQTLs) for culm length were detected in BILs. On the other hand, 17 mQTLs were detected for nine traits in CSSLs. Among them, six mQTLs for grain yield traits were collocated on chromosome 10 in both years. For spikelet fertility, six putative QTLs were detected under high temperature conditions in 2018. The QTLs identified in this study could be used for the development of rice varieties conferring inter-subspecific combinations of yield-related traits.
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Salinity is a common and increasing problem in many coastal rice producing areas around the world. Salinity tolerance at the reproductive stage in rice is crucial as it determines grain yield. An F2 mapping population was developed from two modern rice cultivars contrasting in tolerance: NSIC Rc222 (a high-yielding salt-sensitive variety released in the Philippines) and BRRI dhan 47 (a salt-tolerant variety released in Bangaldesh). The performance of the F2 population showed transgressive segregation in the yield components under salinity stress of EC 10 dS/m under salinized field conditions. Ninety-six single nucleotide polymorphism (SNP) markers using 96-plex FluidigmTM genotyping were used to construct a linkage map of 1306.2 cM (Kosambi), with an average interval size of 13.6 cM. Seven putative quantitative trait loci (QTLs) for reproductive stage salinity tolerance traits having LOD values ranging from 2.9 to 4.1 were identified on chromosomes 1, 2, 5 and 11, explaining 13.4 to 18.4% of the phenotypic variation. Results of this mapping study identified a genomic region on chromosome 2 that confers salinity tolerance at the reproductive stage as measured by the number of filled spikelets, percent filled spikelets and yield. This study reports the molecular mapping of QTLs controlling reproductive-stage salinity tolerance-related traits, which will be useful in marker-assisted selection and breeding population development in rice.
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Low-temperature germinability (LTG) is an important trait for rice direct seeding at temperate and high-altitude region. Previously, five QTLs (quantitative trait loci) for LTG were detected using an interspecific cross population between the Korea
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The
objective
of this study was to detect QTLs for rice seedling traits under normal water (control) and low water conditions (drought stress). Ninety-eight recombinant inbred lines (RILs) from a cross between closely-related japonica cultivars, M-203 and M-206 were grown under both low water and normal water conditions. QTLs for morphological traits were investigated at seedling stage using 5,164 single nucleotide polymorphisms via genotyping-by-sequencing. Twenty-three QTLs were associated with four seedling traits: shoot length (SL), root length (RL), shoot dry weight (SW) and root dry weight (RW), were detected and most QTLs were clustered on chromosome 1, 6, 7 and 11. Under normal water conditions, nine QTLs for seedling traits were detected and M-203 alleles increased all the values. The locations of most QTLs were consistent with genes that regulate or respond to auxin and gibberellin. For drought tolerance, fourteen QTLs were detected including seven for drought stress conditions and seven for relative performance (values from drought stress conditions/normal water conditions). Seven QTLs from drought stress conditions coincided with the loci of previously identified drought tolerance genes. Based on the shoot and root length under drought stress conditions, five lines exhibiting the highest values in common were selected as a drought tolerance group. Those lines exhibited better growth than the parents under drought stress conditions and had QTLs alleles for drought tolerance detected in this study. QTL information and selected lines may be used for improving seedling vigor and drought tolerance of rice in breeding programs.
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Seedling vigor in drought stress conditions is an important characteristic of the dry direct-seeded rice system. The drought stress in the seedling stage disrupts seed germination and delays the establishment of seedlings. However, little is known about the genetic mechanism of seedling vigor in drought conditions. The identification of quantitative trait loci (QTL) was conducted using 162 recombinant inbred lines (RILs) derived from a cross between two rice varieties—a Tongil-type Milyang23 and a temperate japonica Tong88-7. The seedling vigor of these RILs was characterized by measuring 10 morphological traits of the seedlings grown under drought conditions. The Tong88-7 seedlings showed significantly higher values than the Milyang23 seedlings for all traits. The genotyping-by-sequencing method was used to construct a map of 6140 single nucleotide polymorphisms. Six main-effect QTLs (M-QTLs) associated with seedling vigor traits under drought stress were identified on chromosomes 9 and 11. In particular, five out of these six QTLs were located on chromosome 11, explaining the phenotypic variances of 4.3% through 10.1%. In addition, 21 epistatic QTLs (E-QTLs) were detected, and the 27 loci involved in this interaction were distributed on 11 chromosomes. Both M-QTLs and E-QTLs detected in this study would be useful in breeding programs to develop elite rice varieties especially adapted to dry direct-seeded rice system.
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In this study, two near-isogenic lines (NILs) were selected from a series of chromosome segment substitution lines developed from an interspecific cross between
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Supplying sufficient rice to growing populations is a global challenge. Hybrid
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Leafspot is one of the major diseases of peanut (
objective
of this study was to identify and map quantitative trait loci (QTLs) for resistance to leafspot disease. An F2:6 recombinant inbred line (RIL) population, derived from a released cultivar Tamrun OL07 and a highly tolerant breeding line Tx964117, were used as a mapping population. A total of 90 RILs were planted for disease phenotyping in Yoakum, Texas in 2010 and 2012. A genetic map spanning the 20 linkage groups was developed using 1,211 SNP markers based on double digest restriction-site associated DNA sequencing (ddRAD-seq). A total of six quantitative trait loci (QTLs) were identified, with LOD score values of 3.2–5.0 and phenotypic variance explained ranging from 11%–24%. Major QTLs identified in this study may be used as potential targets for peanut improvement to leafspot disease through molecular breeding.
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This study was initiated to identify quantitative trait loci (QTL) involved in root system development by measuring root length and weight of rice seedlings grown in hydroponic culture condition. Growth conditions for estimating the root elongation were set up to supply NH4+ as a single nitrogen source. Four rice accessions and 40 introgression lines (ILs) derived from a cross between ‘Ilpumbyeo’, a temperate
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Bruchid (
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A recombinant inbred line (RIL) population derived from the cross between Ilpumbyeo (a
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Hybrid sterility is the major obstacle that can act as a barrier to genetic recombination and limits favorable gene transfer during inter-subspecific crosses in rice. However, hybrid sterility can be overcome by utilization of wide-compatible varieties (WCV). In the present study, two F2 populations generated from crosses between a wide-compatibility line (HWC-line) and two Korean varieties, Dasan and Hwacheong were evaluated for eight agronomic traits. A total of 157 molecular markers consisted of 116 STS, 40 SSR and 1 FNP were used to create genetic linkage maps spanning all 12 chromosomes. Twenty-one main-effect QTLs (M-QTLs) were identified in HWC-line/Dasan (HD) population. These loci are populated with two QTLs for culm length, one for spikelet per panicle, one for spikelet fertility, four for grain length, five for grain width, five for grain shape, and three for 100 grain-weight. In HWC-line/Hwacheong (HH) population, 17 QTLs were detected including two QTLs for culm length, one for panicle length, one for spikelet fertility, five for grain length, three for grain width, three for grain shape, and two for 100-grain weight. Of the total 34 QTLs found in the two F2 populations, 9 QTLs associated with culm length, grain length, grain width and grain shape were newly identified in this study. These QTLs will be useful for further understanding the genetic basis of agronomic traits and for developing markers for selection in rice breeding. In addition, HWC-line could be used as a bridge for inter-subspecies crosses overcoming hybrid sterility.
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A total of 310 BC2F2 lines derived from the cross of OM5930/N22 were evaluated for heat stress at flowering. Genetic map was set up with 264 polymorphic SSRs to detect linkage to the target traits. The map covers 2,741.63 cM with an average interval of 10.55 cM between two marker loci. Markers associated with heat tolerance were located mostly on chromosomes 3, 4, 6, 8, 10 and 11. The proportion of phenotypic variation explained by each QTL ranged from 17.1% for RM160 to 36.2% for RM3586. Four QTLs were detected for filled grains per panicle on chromosome 4 at the interval of RM468 - RM7076 and RM241 - RM26212, explaining 13.1 and 31.0% of the total phenotypic variation, respectively. Two QTLs controling unfilled grain percentage was also detected at loci RM554 and RM3686 on chromosome 3 explaining 25.0 and 11.2% of the total phenotypic variance. One QTL was detected for 1,000-grain weight located at the locus RM103 on chromosome 6, explaining 30.6% of the total phenotypic variance. Also, a QTL at the locus RM5749 on chromosome 4 was identified which explained 10.8% of the total phenotypic variance of grain yield. A single QTL at the interval of RM3586- RM160 on chromosome 3 was detected in conformity with the QTL findings for heat tolerance in previous studies.
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To utilize the favorable gene(s) from winter wheat for genetic improvement of spring wheat, this study was carried out to identify the quantitative trait loci (QTL) associated with grain protein content (GPC) and grain hardness (GH) by analysis of recombinant inbred lines (RILS) derived from a cross between spring wheat and spring version of winter wheat. A genetic map of 334 loci was constructed which covered 1575.30cM on all 21 chromosomes. Two QTLs on 3B and 5B chromosome were detected for GPC. A QTL identified barc77 on chromosome 3B had additive effect of 0.17 and the other QTL identified by gwm499 on chromosome 5B had additive effect of 0.19. There were two major QTLs for GH identified on Chromosome 1B and chromosome 5A. The QTL on 1B was localized within a 18.7cM region flanked by wmc719 and wmc367-1 with 1.75 additive effect. The QTL on chromosome 5A flanked by SNP markers, IWA6573 and IWA2363, had additive effect of 1.44.
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Eating and cooking qualities are the most important trait in
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Low-temperature stress is an important factor controlling the growth and development of rice (
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