Quantitative Trait Loci Mapping Research Articles

Evolution of a novel adrenal cell type that promotes parental care.

Cell types with specialized functions fundamentally regulate animal behaviour, and yet the genetic mechanisms that underlie the emergence of novel cell types and their consequences for behaviour are not well understood1. Here we show that the monogamous oldfield mouse (Peromyscus polionotus) has recently evolved a novel cell type in the adrenal gland that expresses the enzyme AKR1C18, which converts progesterone into 20α-hydroxyprogesterone. We then demonstrate that 20α-hydroxyprogesterone is more abundant in oldfield mice, where it induces monogamous-typical parental behaviours, than in the closely related promiscuous deer mice (Peromyscus maniculatus). Using quantitative trait locus mapping in a cross between these species, we ultimately find interspecific genetic variation that drives expression of the nuclear protein GADD45A and the glycoprotein tenascin N, which contribute to the emergence and function of this cell type in oldfield mice. Our results provide an example by which the recent evolution of a new cell type in a gland outside the brain contributes to the evolution of social behaviour.

QTL mapping reveals malt barley quality improvement in two dryland environments associated with extended grain fill and seminal root traits

AbstractTo achieve malt grade and receive full price, barley (Hordeum vulgare L.) crops must meet standards for certain quality traits including percent plump and protein. Terminal drought stress reduces quality and is projected to worsen in barley cultivation areas, underscoring the need for varieties that maintain good malt production with unreliable precipitation. The stay‐green trait extends the grain fill phase between heading and maturity and has been linked to stable quality under dry conditions. However, this relationship can be inconsistent and is not well understood. To effectively leverage a longer grain fill phenotype for drought adaptation, a better grasp of its genetics and environmental interaction is needed. Stay‐green root system differences have been observed and could be at play. We performed correlation and quantitative trait locus (QTL) analysis on grain fill duration, grain quality, and seminal root traits using a recombinant inbred line (RIL) population segregating for stay‐green. Agronomic data were collected in four field trials at two distinct semiarid locations, and roots were measured in a greenhouse assay. Earlier heading and later maturity led to improved quality in both locations and more consistent quality between locations. Earlier heading had a greater influence on quality in the drier environment, while later maturity was more impactful in the less dry environment. We observed co‐locations of seminal root trait QTLs with grain fill duration and grain quality. These QTLs lay the groundwork for further investigation into root phenotypes associated with stay‐green and the deployment of these traits in breeding for drought adaptation.

Biofortification for Enhancement of Zinc (Zn) and Iron (Fe) Content in Wheat (Triticum aestivum L.): A Comprehensive Review

Micronutrient deficiency, often termed "hidden hunger," is a significant global health issue affecting over three billion people worldwide. Given that wheat is a primary staple grain in many developing countries, it is crucial to focus on enhancing its nutritional content, as it often lacks essential micronutrients. Biofortification offers a promising solution to this problem by increasing the levels of key nutrients in the edible parts of crops through both agronomic and genetic approaches. This article examines the potential of biofortification in wheat, targeting vital micronutrients like iron and zinc. By employing traditional breeding methods alongside modern genetic techniques such as genome sequencing, Quantitative Trait Locus (QTL) mapping, and Genome Wide Association Studies (GWAS), researchers aim to boost the bioavailability and concentration of these nutrients in wheat varieties. The genetic variability observed in wild wheat relatives plays a significant role in identifying traits that can enhance the nutritional profile of wheat. The benefits of biofortified wheat are numerous, especially for resource-limited consumers who rely heavily on cereal-based diets. Increased concentrations of iron and zinc in wheat could improve the health and well-being of these populations, helping to combat hidden hunger on a global scale. This review paper provides a comprehensive overview of the current state of agronomic and genetic strategies for wheat biofortification, with a specific focus on increasing zinc and iron content in wheat grains. It discusses the progress made in biofortification research and outlines the various breeding approaches and genetic tools used to enhance wheat's nutritional content. By leveraging these strategies, wheat biofortification has the potential to address micronutrient deficiencies and contribute to improved public health outcomes worldwide.

QTL Mapping and Candidate Gene Mining for Stem Diameter Using Genetic Basis of Cultivated Soybean and Wild Soybean

Soybean (Glycine max) is a vital food crop, serving as a major source of high-quality protein for human and animal consumption. Stem diameter is one of the primary determinants of the stem lodging resistance of a given plant, but there has been relatively little research to date focused on genes associated with this trait. To address this gap in the literature, 207 chromosome segment substitution lines (CSSLs) were generated in the present study through the crossing and backcrossing of the improved Suinong14 and the wild ZYD00006 soybean varieties. These CSSLs were then used for the mapping of quantitative trait loci (QTLs) associated with stem diameter in two-year field planting materials, leading to the identification of nine QTLs. Whole genome resequencing, RNA-seq, and qPCR were then used to evaluate candidate genes associated with stem diameter within these QTL intervals, ultimately leading to the selection of Glyma.04G004100 as a stem diameter-related gene. Subsequent qPCR analyses revealed that Glyma.04g004100 was upregulated in soybean plants with larger stem diameters, and haplotype analyses yielded results consistent with these stem diameter data in the population used to conduct this study. In summary, a series of QTLs associated with stem diameter were identified in the present study, resulting in the establishment of Glyma.04g004100 as a stem diameter-related gene. Together, these results offer a theoretical foundation for the future molecular-assisted breeding of lodging-resistant soybean varieties, and future functional research focused on Glyma.04g004100 may elucidate the molecular mechanisms and key signaling networks involved in soybean stem development.

High-density genetic map construction and QTL mapping of a zigzag-shaped stem trait in tea plant (Camellia sinensis)

The highly unique zigzag-shaped stem phenotype in tea plants boasts significant ornamental value and is exceptionally rare. To investigate the genetic mechanism behind this trait, we developed BC1 artificial hybrid populations. Our genetic analysis revealed the zigzag-shaped trait as a qualitative trait. Utilizing whole-genome resequencing, we constructed a high-density genetic map from the BC1 population, incorporating 5,250 SNP markers across 15 linkage groups, covering 3,328.51 cM with an average marker interval distance of 0.68 cM. A quantitative trait locus (QTL) for the zigzag-shaped trait was identified on chromosome 4, within a 61.2 to 97.2 Mb range, accounting for a phenotypic variation explained (PVE) value of 13.62%. Within this QTL, six candidate genes were pinpointed. To better understand their roles, we analyzed gene expression in various tissues and individuals with erect and zigzag-shaped stems. The results implicated CsXTH (CSS0035625) and CsCIPK14 (CSS0044366) as potential key contributors to the zigzag-shaped stem formation. These discoveries lay a robust foundation for future functional genetic mapping and tea plant genetic enhancement.

Inheritance analysis of major lignan contents in Schisandra chinensis hybrid progeny

Schisandra chinensis (Turcz.) Baill. has been used in traditional Chinese medicine for more than 2000 years and is classified as a superior herb. To examine the inheritance of lignan content traits, we measured the contents of six lignan constituents in the fruit and stem of 142 individuals from the cross ‘Jinwuwei 1’ × ‘Zaohong’ for three successive years. The optimal genetic model for each trait was screened using a mixed major gene + polygene inheritance model. The lignan contents differed in degree of variation, with the annual average coefficient of variation ranging from 22.31% to 79.80% across the three years. Significant transgressive heterosis was observed for schisandrol B content both in the fruit and stem, whereas negative heterosis was detected for γ-schisandrin content both in the fruit and stem. The optimal genetic models were inconsistent among different lignans in the same organ and between different organs for the same lignan, which may be associated with specific gene expression patterns. The additive effects of the lignan contents were mostly positive, whereas the dominance effects were mainly negative. The results of this study provide a theoretical basis for quantitative trait locus mapping and marker-assisted breeding of lignan contents in S. chinensis.

Rapid Mapping of Quantitative Trait Loci for the Growth Habit in Peanuts Using Bulked Segregant Analysis

Rapid Mapping of Quantitative Trait Loci for the Growth Habit in Peanuts Using Bulked Segregant Analysis

Mapping QTLs for adult-plant resistance to powdery mildew and stripe rust using a recombinant inbred line population derived from cross Qingxinmai × 041133

A recombinant inbred line (RIL) population derived from wheat landrace Qingxinmai and breeding line 041133 exhibited segregation in resistance to powdery mildew and stripe rust in five and three field tests, respectively. A 16K genotyping by target sequencing (GBTS) single-nucleotide polymorphism (SNP) array-based genetic linkage map was used to dissect the quantitative trait loci (QTLs) for disease resistance. Four and seven QTLs were identified for adult-plant resistance (APR) against powdery mildew and stripe rust. QPm.caas-1B and QPm.caas-5A on chromosomes 1B and 5A were responsible for the APR against powdery mildew in line 041133. QYr.caas-1B, QYr.caas-3B, QYr.caas-4B, QYr.caas-6B.1, QYr.caas-6B.2, and QYr.caas-7B detected on the five B-genome chromosomes of line 041133 conferred its APR to stripe rust. QPm.caas-1B and QYr.caas.1B were co-localized with the pleiotropic locus Lr46/Yr29/Sr58/Pm39/Ltn2. A Kompetitive Allele Specific Polymorphic (KASP) marker KASP_1B_668028290 was developed to trace QPm/Yr.caas.1B. Four lines pyramiding six major disease resistance loci, PmQ, Yr041133, QPm/Yr.caas-1B, QPm.caas-2B.1, QYr.caas-3B, and QPm.caas-6B, were developed. They displayed effective resistance against both powdery mildew and stripe rust at the seedling and adult-plant stages.

Molecular breeding of flower load related traits in dioecious autotetraploid Actinidia arguta

Flowering plants exhibit a wide range of sexual reproduction systems, with the majority being hermaphroditic. However, some plants, such as Actinidia arguta (kiwiberry), have evolved into dioecious species with distinct female and male vines. In this study, we investigated the flower load and growth habits of female kiwiberry genotypes to identify the genetic basis of high yield with low maintenance requirements. Owing to the different selection approaches between female and male genotypes, we further extended our study to male kiwiberry genotypes. By combining both investigations, we present a novel breeding tool for dioecious crops. A population of A. arguta seedlings was phenotyped for flower load traits, in particular the proportion of non-floral shoots, proportion of floral shoots, and average number of flowers per floral shoot. Quantitative trait locus (QTL) mapping was used to analyse the genetic basis of these traits. We identified putative QTLs on chromosome 3 associated with flower-load traits. A pleiotropic effect of the male-specific region of the Y chromosome (MSY) on chromosome 3 affecting flower load-related traits between female and male vines was observed in an A. arguta breeding population. Furthermore, we utilized Genomic Best Linear Unbiased Prediction (GBLUP) to predict breeding values for the quantitative traits by leveraging genomic data. This approach allowed us to identify and select superior genotypes. Our findings contribute to the understanding of flowering and fruiting dynamics in Actinidia species, providing insights for kiwiberry breeding programs aiming to improve yield through the utilization of genomic methods and trait mapping.

Complementation testing identifies genes mediating effects at quantitative trait loci underlying fear-related behavior

Knowing the genes involved in quantitative traits provides an entry point to understanding the biological bases of behavior, but there are very few examples where the pathway from genetic locus to behavioral change is known. To explore the role of specific genes in fear behavior, we mapped three fear-related traits, tested fourteen genes at six quantitative trait loci (QTLs) by quantitative complementation, and identified six genes. Four genes, Lamp, Ptprd, Nptx2, and Sh3gl, have known roles in synapse function; the fifth, Psip1, was not previously implicated in behavior; and the sixth is a long non-coding RNA, 4933413L06Rik, of unknown function. Variation in transcriptome and epigenetic modalities occurred preferentially in excitatory neurons, suggesting that genetic variation is more permissible in excitatory than inhibitory neuronal circuits. Our results relieve a bottleneck in using genetic mapping of QTLs to uncover biology underlying behavior and prompt a reconsideration of expected relationships between genetic and functional variation.

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.

Advancements of Breeding and Genomics in Wheat (Triticum aestivum L.): Enhancing Yield and Nutritional Value for Sustainable Agriculture

Advancements in wheat breeding and genomics presently explores the genomic interventions driving focusing on quantitative trait loci (QTL) mapping, marker-assisted selection (MAS) and genomic selection (GS). QTL mapping emerges as a pivotal method for pinpointing markers linked with desirable traits, facilitating MAS. Furthermore, genomic selection (GS) holds immense potential for crop improvement. It also delves into the current landscape of MAS and explores various prospects of GS for wheat biofortification. Looking ahead, accelerated mapping studies combined with MAS and GS schemes are poised to further enhance wheat breeding efficiency. Dense molecular maps and a large set of ESTs (Expressed Sequence Tags) have enabled genome-wide identification of gene-rich and gene-poor regions, as well as QTL, including eQTL (Expression quantitative trait loci). Additionally, markers associated with major economic traits have facilitated MAS programs in some countries and enabled map-based cloning of several genes/QTL. Resources for functional genomics, such as TILLING and RNA interference (RNAi), alongside emerging approaches like epigenetics and association mapping, are further enriching wheat genomics research. In this review, we initially present cutting-edge genome-editing technologies in crop plants, with a specific focus on wheat, addressing both functional genomics and genetic enhancement. We subsequently delineate the utilization of additional technologies, including GWAS, high-throughput genotyping and phenotyping, speed breeding, and synthetic biology, within the context of wheat breeding. We assert that integrating genome editing with other molecular breeding strategies will significantly expedite the genetic enhancement of wheat, thus contributing to sustainable global production.

Genome-wide QTL and eQTL mapping reveal genes associated with growth rate trait of the Pacific white shrimp (Litopenaeus vannamei)

BackgroundGrowth rate is a crucial economic trait for farmed animals, but the genetic regulation of this trait is largely unknown in non-model organisms such as shrimp.ResultsIn this study, we performed genome-wide phenotypic quantitative trait loci (QTL) and expression quantitative trait loci (eQTL) mapping analyses to identify genes affecting the growth rate of Pacific white shrimp (Litopenaeus vannamei), which is the most commercially-farmed crustacean worldwide. We used RNA-sequencing of 268 individuals in a mapping population, and subsequently validated our findings through gene silencing and shrimp growth experiments. We constructed a high-density genetic linkage map comprising 5533 markers spanning 44 linkage groups, with a total distance of 6205.75 cM and an average marker interval of 1.12 cM. Our analyses identified 11 QTLs significantly correlated with growth rate, and 117,525 eQTLs. By integrating QTL and eQTL data, we identified a gene (metalloreductase STEAP4) highly associated with shrimp growth rate. RNA interference (RNAi) analysis and growth experiments confirmed that STEAP4 was significantly correlated with growth rate in L. vannamei.ConclusionsOur results indicate that the comprehensive analysis of QTL and eQTL can effectively identify genes involved in complex animal traits. This is important for marker-assisted selection (MAS) of animals. Our work contributes to the development of shrimp breeding and available genetic resources.

An aldehyde dehydrogenase gene, GhALDH7B4_A06, positively regulates fiber strength in upland cotton (Gossypium hirsutum L.).

High fiber strength (FS) premium cotton has significant market demand. Consequently, enhancing FS is a major objective in breeding quality cotton. However, there is a notable lack of known functionally applicable genes that can be targeted for breeding. To address this issue, our study used specific length-amplified fragment sequencing combined with bulk segregant analysis to study FS trait in an F2 population. Subsequently, we integrated these results with previous quantitative trait locus mapping results regarding fiber quality, which used simple sequence repeat markers in F2, F2:3, and recombinant inbred line populations. We identified a stable quantitative trait locus qFSA06 associated with FS located on chromosome A06 (90.74-90.83 Mb). Within this interval, we cloned a gene, GhALDH7B4_A06, which harbored a critical mutation site in coding sequences that is distinct in the two parents of the tested cotton line. In the paternal parent Ji228, the gene is normal and referred to as GhALDH7B4_A06O; however, there is a nonsense mutation in the maternal parent Ji567 that results in premature termination of protein translation, and this gene is designated as truncated GhALDH7B4_A06S. Validation using recombinant inbred lines and gene expression analysis revealed that this mutation site is correlated with cotton FS. Virus-induced gene silencing of GhALDH7B4 in cotton caused significant decreases in FS and fiber micronaire. Conversely, GhALDH7B4_A06O overexpression in Arabidopsis boosted cell wall component contents in the stem. The findings of our study provide a candidate gene for improving cotton fiber quality through molecular breeding.

A combination of QTL mapping and genome-wide association study revealed the key gene for husk number in maize.

Two key genes Zm00001d021232 and Zm00001d048138 were identified by QTL mapping and GWAS. Additionally, they were verified to be significantly associated with maize husk number (HN) using gene-based association study. As a by-product of maize production, maize husk is an important industrial raw material. Husk layer number (HN) is an important trait that affects the yield of maize husk. However, the genetic mechanism underlying HN remains unclear. Herein, a total of 13 quantitative trait loci (QTL) controlling HN were identified in an IBM Syn 10 DH population across different locations. Among these, three QTL were individually repeatedly detected in at least two environments. Meanwhile, 26 unique single nucleotide polymorphisms (SNPs) were detected to be significantly (p < 2.15 × 10-6) associated with HN in an association pool. Of these SNPs, three were simultaneously detected across multiple environments or environments and best linear unbiased prediction (BLUP). We focused on these environment-stable and population-common genetic loci for excavating the candidate genes responsible for maize HN. Finally, 173 initial candidate genes were identified, of which 22 were involved in both multicellular organism development and single-multicellular organism process and thus confirmed as the candidate genes for HN. Gene-based association analyses revealed that the variants in four genes were significantly (p < 0.01/N) correlated with HN, of which Zm00001d021232 and Zm00001d048138 were highly expressed in husks and early developing ears among different maize tissues. Our study contributes to the understanding of genetic and molecular mechanisms of maize husk yield and industrial development in the future.

Genetic analysis and QTL mapping for pericarp thickness in maize (Zea mays L.)

Proper pericarp thickness protects the maize kernel against pests and diseases, moreover, thinner pericarp improves the eating quality in fresh corn. In this study, we aimed to investigate the dynamic changes in maize pericarp during kernel development and identified the major quantitative trait loci (QTLs) for maize pericarp thickness. It was observed that maize pericarp thickness first increased and then decreased. During the growth and formation stages, the pericarp thickness gradually increased and reached the maximum, after which it gradually decreased and reached the minimum during maturity. To identify the QTLs for pericarp thickness, a BC4F4 population was constructed using maize inbred lines B73 (recurrent parent with thick pericarp) and Baimaya (donor parent with thin pericarp). In addition, a high-density genetic map was constructed using maize 10 K SNP microarray. A total of 17 QTLs related to pericarp thickness were identified in combination with the phenotypic data. The results revealed that the heritability of the thickness of upper germinal side of pericarp (UG) was 0.63. The major QTL controlling UG was qPT1-1, which was located on chromosome 1 (212,215,145–212,948,882). The heritability of the thickness of upper abgerminal side of pericarp (UA) was 0.70. The major QTL controlling UA was qPT2-1, which was located on chromosome 2 (2,550,197–14,732,993). In addition, a combination of functional annotation, DNA sequencing analysis and quantitative real-time PCR (qPCR) screened two candidate genes, Zm00001d001964 and Zm00001d002283, that could potentially control maize pericarp thickness. This study provides valuable insights into the improvement of maize pericarp thickness during breeding.

QTL for the Kinematic Traits That Define the Arabidopsis Root Elongation Zone and Their Relationship to Gravitropism.

Cell expansion in a discrete region called the elongation zone drives root elongation. Analyzing time lapse images can quantify the expansion in kinematic terms as if it were fluid flow. We used horizontal microscopes to collect images from which custom software extracted the length of the elongation zone, the peak relative elemental growth rate (REGR) within it, the axial position of the REGR peak, and the root elongation rate. Automation enabled these kinematic traits to be measured in 1575 Arabidopsis seedlings representing 162 recombinant inbred lines (RILs) derived from a cross of Cvi and Ler ecotypes. We mapped ten quantitative trait loci (QTL), affecting the four kinematic traits. Three QTL affected two or more traits in these vertically oriented seedlings. We compared this genetic architecture with that previously determined for gravitropism using the same RIL population. The major QTL peaks for the kinematic traits did not overlap with the gravitropism QTL. Furthermore, no single kinematic trait correlated with quantitative descriptors of the gravitropism response curve across this population. In addition to mapping QTL for growth zone traits, this study showed that the size and shape of the elongation zone may vary widely without affecting the differential growth induced by gravity.

Multimodal joint deconvolution and integrative signature selection in proteomics

Deconvolution is an efficient approach for detecting cell-type-specific (cs) transcriptomic signals without cellular segmentation. However, this type of methods may require a reference profile from the same molecular source and tissue type. Here, we present a method to dissect bulk proteome by leveraging tissue-matched transcriptome and proteome without using a proteomics reference panel. Our method also selects the proteins contributing to the cellular heterogeneity shared between bulk transcriptome and proteome. The deconvoluted result enables downstream analyses such as cs-protein Quantitative Trait Loci (cspQTL) mapping. We benchmarked the performance of this multimodal deconvolution approach through CITE-seq pseudo bulk data, a simulation study, and the bulk multi-omics data from human brain normal tissues and breast cancer tumors, individually, showing robust and accurate cell abundance quantification across different datasets. This algorithm is implemented in a tool MICSQTL that also provides cspQTL and multi-omics integrative visualization, available at https://bioconductor.org/packages/MICSQTL.

QTL mapping for the flag leaf-related traits using RILs derived from Trititrigia germplasm line SN304 and wheat cultivar Yannong15 in multiple environments

BackgroundDeveloping and enriching genetic resources plays important role in the crop improvement. The flag leaf affects plant architecture and contributes to the grain yield of wheat (Triticum aestivum L.). The genetic improvement of flag leaf traits faces problems such as a limited genetic basis. Among the various genetic resources of wheat, Thinopyrum intermedium has been utilized as a valuable resource in genetic improvement due to its disease resistance, large spikes, large leaves, and multiple flowers. In this study, a recombinant inbred line (RIL) population was derived from common wheat Yannong15 and wheat-Th. intermedium introgression line SN304 was used to identify the quantitative trait loci (QTL) for flag leaf-related traits.ResultsQTL mapping was performed for flag leaf length (FLL), flag leaf width (FLW) and flag leaf area (FLA). A total of 77 QTLs were detected, and among these, 51 QTLs with positive alleles were contributed by SN304. Fourteen major QTLs for flag leaf traits were detected on chromosomes 2B, 3B, 4B, and 2D. Additionally, 28 QTLs and 8 QTLs for flag leaf-related traits were detected in low-phosphorus and drought environments, respectively. Based on major QTLs of positive alleles from SN304, we identified a pair of double-ended anchor primers mapped on chromosome 2B and amplified a specific band of Th. intermedium in SN304. Moreover, there was a major colocated QTL on chromosome 2B, called QFll/Flw/Fla-2B, which was delimited to a physical interval of approximately 2.9 Mb and contained 20 candidate genes. Through gene sequence and expression analysis, four candidate genes associated with flag leaf formation and growth in the QTL interval were identified.ConclusionThese results promote the fine mapping of QFll/Flw/Fla-2B, which have pleiotropic effects, and will facilitate the identification of candidate genes for flag leaf-related traits. Additionally, this work provides a theoretical basis for the application of Th. intermedium in wheat breeding.

Identification of quantitative trait loci associated with leaf rust resistance in rye by precision mapping

BackgroundLeaf rust (LR) is among the most destructive fungal diseases of rye (Secale cereale L.). Despite intensive research using various analytical and methodological approaches, such as quantitative trait locus (QTL) mapping, candidate gene expression analysis, and transcriptome sequencing, the genetic basis of the rye immune response to LR remains unclear.ResultsA genome-wide association study was employed to detect QTLs controlling the immune response to LR of rye. A mapping population, G38A, was constructed by crossing two inbred lines: 723 (susceptible to LR) and JKI-NIL-Pr3 (a donor of the LR resistance gene Pr3). For genotyping, SNP-DArT and silico-DArT markers were used. Resistance phenotyping was conducted by visual assessment of the infection severity in detached leaf segments inoculated with two isolates of Puccinia recondita f. sp. secalis, namely, 60/17/2.1 (isolate S) in the main experiment and 86/n/2.1_5x (isolate N) in the validation experiment, at 10 and 17 days post-infection (dpi), respectively.In total, 42,773 SNP-DArT and 105,866 silico-DArT markers were included in the main analysis including isolate S, of which 129 and 140 SNP-DArTs and 767 and 776 silico-DArTs were significantly associated (p ≤ 0.001; − log10(p) ≥ 3.0) with the immune response to LR at 10 and 17 dpi, respectively. Most significant markers were mapped to chromosome 1R. The number of common markers from both systems and at both time points occupying common chromosomal positions was 37, of which 21 were positioned in genes, comprising 18 markers located in exons and three in introns. This gene pool included genes encoding proteins with a known function in response to LR (e.g., a NBS-LRR disease resistance protein-like protein and carboxyl-terminal peptidase).ConclusionThis study has expanded and supplemented existing knowledge of the genetic basis of rye resistance to LR by (1) detecting two QTLs associated with the LR immune response of rye, of which one located on the long arm of chromosome 1R is newly detected, (2) assigning hundreds of markers significantly associated with the immune response to LR to genes in the ‘Lo7’ genome, and (3) predicting the potential translational effects of polymorphisms of SNP-DArT markers located within protein-coding genes.