Related Recombinant Inbred Line Research Articles

High-Resolution Mapping in Two RIL Populations Refines Major "QTL Hotspot" Regions for Seed Size and Shape in Soybean (Glycine max L.).

Seed size and shape are important traits determining yield and quality in soybean. However, the genetic mechanism and genes underlying these traits remain largely unexplored. In this regard, this study used two related recombinant inbred line (RIL) populations (ZY and K3N) evaluated in multiple environments to identify main and epistatic-effect quantitative trait loci (QTLs) for six seed size and shape traits in soybean. A total of 88 and 48 QTLs were detected through composite interval mapping (CIM) and mixed-model-based composite interval mapping (MCIM), respectively, and 15 QTLs were common among both methods; two of them were major (R2 > 10%) and novel QTLs (viz., qSW-1-1ZN and qSLT-20-1K3N). Additionally, 51 and 27 QTLs were identified for the first time through CIM and MCIM methods, respectively. Colocalization of QTLs occurred in four major QTL hotspots/clusters, viz., “QTL Hotspot A”, “QTL Hotspot B”, “QTL Hotspot C”, and “QTL Hotspot D” located on Chr06, Chr10, Chr13, and Chr20, respectively. Based on gene annotation, gene ontology (GO) enrichment, and RNA-Seq analysis, 23 genes within four “QTL Hotspots” were predicted as possible candidates, regulating soybean seed size and shape. Network analyses demonstrated that 15 QTLs showed significant additive x environment (AE) effects, and 16 pairs of QTLs showing epistatic effects were also detected. However, except three epistatic QTLs, viz., qSL-13-3ZY, qSL-13-4ZY, and qSW-13-4ZY, all the remaining QTLs depicted no main effects. Hence, the present study is a detailed and comprehensive investigation uncovering the genetic basis of seed size and shape in soybeans. The use of a high-density map identified new genomic regions providing valuable information and could be the primary target for further fine mapping, candidate gene identification, and marker-assisted breeding (MAB).

Deciphering the Genetic Architecture of Plant Height in Soybean Using Two RIL Populations Sharing a Common M8206 Parent.

Plant height (PH) is an important agronomic trait that is closely related to soybean yield and quality. However, it is a complex quantitative trait governed by multiple genes and is influenced by environment. Unraveling the genetic mechanism involved in PH, and developing soybean cultivars with desirable PH is an imperative goal for soybean breeding. In this regard, the present study used high-density linkage maps of two related recombinant inbred line (RIL) populations viz., MT and ZM evaluated in three different environments to detect additive and epistatic effect quantitative trait loci (QTLs) as well as their interaction with environments for PH in Chinese summer planting soybean. A total of eight and 12 QTLs were detected by combining the composite interval mapping (CIM) and mixed-model based composite interval mapping (MCIM) methods in MT and ZM populations, respectively. Among these QTLs, nine QTLs viz., QPH-2, qPH-6-2MT, QPH-6, qPH-9-1ZM, qPH-10-1ZM, qPH-13-1ZM, qPH-16-1MT, QPH-17 and QPH-19 were consistently identified in multiple environments or populations, hence were regarded as stable QTLs. Furthermore, Out of these QTLs, three QTLs viz., qPH-4-2ZM, qPH-15-1MT and QPH-17 were novel. In particular, QPH-17 could detect in both populations, which was also considered as a stable and major QTL in Chinese summer planting soybean. Moreover, eleven QTLs revealed significant additive effects in both populations, and out of them only six showed additive by environment interaction effects, and the environment-independent QTLs showed higher additive effects. Finally, six digenic epistatic QTLs pairs were identified and only four additive effect QTLs viz., qPH-6-2MT, qPH-19-1MT/QPH-19, qPH-5-1ZM and qPH-17-1ZM showed epistatic effects. These results indicate that environment and epistatic interaction effects have significant influence in determining genetic basis of PH in soybean. These results would not only increase our understanding of the genetic control of plant height in summer planting soybean but also provide support for implementing marker assisted selection (MAS) in developing cultivars with ideal plant height as well as gene cloning to elucidate the mechanisms of plant height.

Quantitative trait locus mapping for panicle exsertion length in common wheat using two related recombinant inbred line populations

The improvement of panicle exsertion length (PEL) in wheat (Triticum aestivum L.) breeding programs is an emerging objective to improve yield potential, and serves as a complement to the wheat ideotype. In this study we aimed to advance the current understanding of genetic mechanisms underlying panicle exsertion in wheat. Two related recombinant inbred line populations sharing common parent H461 were used to identify and compare quantitative trait loci (QTL) controlling PEL. Using two high-density genetic linkage maps, 13 putative QTL for PEL were detected on chromosomes 1B, 1D, 2B, 2D, 4A, 4B, 5B, 6D, 7A, and 7B; each QTL explained 5.7–15.6% of the phenotypic variation. Among these 13 QTL, nine were independent; the other two pairs derived from H461 were validated to be common QTL based on newly developed high-resolution melt markers. Further, plant height (PH) was measured to perform covariance QTL analysis with eight major QTL; three of them derived from the wheat variety CM107 were not affected by PH. Pleiotropic effects on yield-related traits (PH, spike length, spikelet number per spike, spikelet density, kernel number per spike, kernel length, and thousand kernel weight) of the eight major QTL were also evaluated. These eight QTL may be valuable for fine mapping and marker-assisted selection in wheat breeding programs.

Detection of quantitative trait loci for wheat (Triticum aestivumL.) heading and flowering date

AbstractHeading date (HD) and flowering date (FD) are critical for yield potential and stability, so understanding their genetic foundation is of great significance in wheat breeding. Three related recombinant inbred line populations with a common female parent were developed to identify quantitative trait loci (QTL) for HD and FD in four environments. In total, 25 putative additive QTL and 20 pairwise epistatic effect QTL were detected in four environments. The additive QTL were distributed across 17 wheat chromosomes. Of these,QHd-1A,QHd-1D,QHd-2B,QHd-3B,QHd-4A,QHd-4BandQHd-6Dwere major and stable QTL for HD.QFd-1A,QFd-2B,QFd-4AandQFd-4Bwere major and stable QTL for FD. In addition, an epistatic interaction test showed that epistasis played important roles in controlling wheat HD and FD. Genetic relationships between HD/FD and five yield-related traits (YRTs) were characterized and ten QTL clusters (C1–C10) simultaneously controlling YRTs and HD/FD were identified. The present work laid a genetic foundation for improving yield potential in wheat molecular breeding programmes.

QTL for flag leaf size and their influence on yield-related traits in wheat

Flag leaf-related traits (FLRTs) are determinant traits affecting plant architecture and yield potential in wheat (Triticum aestivum L.). In this study, three related recombinant inbred line (RIL) populations with a common female parent were developed to identify quantitative trait loci (QTL) for flag leaf width (FLW), length (FLL), and area (FLA) in four environments. A total of 31 QTL were detected in four environments. Two QTL for FLL on chromosomes 3B and 4A (QFll-3B and QFll-4A) and one for FLW on chromosome 2A (QFlw-2A) were major stable QTL. Ten QTL clusters (C1–C10) simultaneously controlling FLRTs and yield-related traits (YRTs) were identified. To investigate the genetic relationship between FLRTs and YRTs, correlation analysis was conducted. FLRTs were found to be positively correlated with YRTs especially with kernel weight per spike and kernel number per spike in all the three RIL populations and negatively correlated with spike number per plant. Appropriate flag leaf size could benefit the formation of high yield potential. This study laid a genetic foundation for improving yield potential in wheat molecular breeding programs.

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.

QTL mapping for heading date, leaf area and chlorophyll content under cold and drought stress in two related recombinant inbred line populations (Japonica rice) and meta‐analysis

AbstractRice is highly susceptible to drought and cold. The goal of this study was to identify the QTLs affecting the rice heading date (HD), leaf area (LA) and chlorophyll content (CC) under cold and drought stress. A total of twenty‐nine and thirty‐eight additive QTLs were detected from two crosses of ‘Dongnong422’/‘Kongyu131’ and ‘Xiaobaijingzi’/‘Kongyu131’, respectively. qHD1‐7‐1, qHD1‐7‐2, qHD1‐2‐1, qLA1‐7‐1, qLA1‐6‐3 and qCC1‐7‐1 show adaptive effects under cold treatment, while qHD2‐2‐3, qHD2‐2‐2, qLA2‐7‐3 and qCC2‐5‐1 were important for explaining the genetic mechanism during drought tolerance. Additionally, nine and five additive × environment interaction QTLs were detected for two RILs, respectively. RIL26 and RIL73 were two lines that are associated with cold and drought for HD. 339 QTLs related to HD, CC and LA of rice from database and our research were projected onto the genetic map. Nine cloned genes and nineteen homologous candidate genes related to HD, CC, cold tolerance and drought tolerance were mapped by meta‐analysis. These results lay the foundation for the fine mapping of QTLs related to HD, LA and CC for marker‐assisted selection.

Shared Genomic Regions Between Derivatives of a Large Segregating Population of Maize Identified Using Bulked Segregant Analysis Sequencing and Traditional Linkage Analysis.

Delayed transition from the vegetative stage to the reproductive stage of development and increased plant height have been shown to increase biomass productivity in grasses. The goal of this project was to detect quantitative trait loci using extremes from a large synthetic population, as well as a related recombinant inbred line mapping population for these two traits. Ten thousand individuals from a B73 × Mo17 noninbred population intermated for 14 generations (IBM Syn14) were grown at a density of approximately 16,500 plants ha−1. Flowering time and plant height were measured within this population. DNA was pooled from the 46 most extreme individuals from each distributional tail for each of the traits measured and used in bulk segregant analysis (BSA) sequencing. Allelic divergence at each of the ∼1.1 million SNP loci was estimated as the difference in allele frequencies between the selected extremes. Additionally, 224 intermated B73 × Mo17 recombinant inbred lines were concomitantly grown at a similar density adjacent to the large synthetic population and were assessed for flowering time and plant height. Using the BSA sequencing method, 14 and 13 genomic regions were identified for flowering time and plant height, respectively. Linkage mapping with the RIL population identified eight and three regions for flowering time and plant height, respectively. Of the regions identified, three colocalized between the two populations for flowering time and two colocalized for plant height. This study demonstrates the utility of using BSA sequencing for the dissection of complex quantitative traits important for production of lignocellulosic ethanol.

Detection of quantitative trait loci (QTLs) for seedling traits and drought tolerance in wheat using three related recombinant inbred line (RIL) populations

In order to detect quantitative trait loci (QTLs) for drought tolerance in wheat during seed germination conditional and unconditional QTL analyses of eight seedling traits were conducted under two water regimes using three related F9 recombinant inbred line populations with a common female parent. A total of 87 QTLs for the eight seedlings traits and 34 specific QTLs related to drought tolerance were detected. Seventy-one of these QTLs were major QTLs with contributions to phenotypic variance of >10 %. Of the 34 QTLs related to drought tolerance only eight were also detected by unconditional analysis of seedling traits under osmotic stress conditions indicating that most of the QTLs related to drought tolerance could not be detected by unconditional QTL analysis. Therefore, conditional QTL analysis of stress-tolerance traits such as drought tolerance was feasible and effective. Of 11 important QTL clusters located on chromosomes 1BL, 1D, 2A, 2B, 2D, 4A, 6B, and 7B, nine were detected in multiple populations and eight were detected by both unconditional and conditional analyses.

QTL detection of seven quality traits in wheat using two related recombinant inbred line populations

Grain protein content (GPC) and gluten quality are the most important factors determining the end-use quality of wheat for pasta-making. Both GPC and gluten quality are considered to be polygenic traits influenced by environmental factors and other agricultural practices. Two related F8:9 recombinant inbred line (RIL) populations were generated to localise genetic factors controlling seven quality traits: GPC, wet gluten content (WGC), flour whiteness (FW), kernel hardness (KH), water absorption (Abs), dough development time (DDT) and dough stability time (DST). These lines were derived by crossing Weimai 8 and Jimai 20 (WJ) and by crossing Weimai 8 and Yannong 19 (WY). In total, WJ comprised 485 lines, while WY comprised 229 lines. Data on these seven quality traits were collected from each line in five different environments. Up to 85 putative QTLs for the seven traits were detected in WJ and 65 putative QTLs were detected in WY. Of these QTLs, 31 QTLs (36.47%) were detected in at least two trials in WJ, while 24 QTLs (36.92%) were detected in at least two trials in WY. Three QTLs from WJ and 25 from WY accounted for more than 10% of the phenotypic variance. The total 150 QTLs were spread throughout all 21 wheat chromosomes. Of these, at least thirteen pairwise were common to both populations, accounting for 20.00 and 15.29% of the total QTLs in WJ and WY, respectively. A major QTL for GPC, accounting for 53.04% of the phenotypic variation, was detected on chromosome 5A. A major QTL for WGC also shared this interval, explained more than 36% of the phenotypic variation, and was significant in two environments. Though co-located QTLs were common, every trait had its unique control mechanism, even for two closely related traits. Due to the different sizes of the two line populations, we also assessed the effects of population size on the efficiency and precision of QTL detection. In sum, this study will enhance our understanding of the genetic basis of these seven pivotal quality traits and facilitate the breeding of improved wheat varieties.