Location Of Quantitative Trait Loci Research Articles

Plasma genome-wide mendelian randomization identifies potentially causal genes in idiopathic pulmonary fibrosis

BackgroundIdiopathic pulmonary fibrosis (IPF) is a complex lung disease with a very poor prognosis. Existing drugs for the treatment of IPF are still insufficient. Therefore, there is still a need to explore new drug targets for preventing and treating IPF.MethodsWe included quantitative trait loci (QTL) for genes, DNA methylation, and proteins in plasma, as well as the summary statistics for IPF. Genetic variants located within 500 kb of the gene and strongly associated with plasma exposure were used as instrumental variables. The causal association between plasma exposures and IPF was primarily estimated using summary-data-based Mendelian randomization (SMR) analysis. Five other MR methods and sensitivity analyses were employed to validate the SMR results. Bayesian tests for colocalization between QTL and IPF risk loci further strengthen the MR results.ResultsWe identified three genes and five DNA methylation sites causally associated with IPF by SMR analysis, validation of MR analysis, sensitivity analysis, and colocalization analysis. BTRC and LINC01252 were negatively associated with IPF risk (OR: 0.30, 95% CI: 0.17–0.54, FDRSMR = 0.029; OR: 0.85, 95% CI: 0.78–0.92, FDRSMR = 0.043), and RIPK4 was positively associated with IPF risk (OR: 2.60, 95% CI: 1.64–4.12, FDRSMR = 0.031). cg00045227 (OR8U8, OR: 1.16, 95% CI: 1.08–1.24, FDRSMR = 0.010), cg00577578 (GBAP1, OR: 1.23, 95% CI: 1.12–1.36, FDRSMR = 0.014), cg14222479 (ARPM1, OR: 3.17, 95% CI: 1.98–5.08, FDRSMR = 0.001), and cg19263494 (PMF1, OR: 1.20, 95% CI: 1.10–1.30, FDRSMR = 0.012) were positively associated with the risk of IPF, whereas cg07163735 (MAPT, OR: 0.22, 95% CI: 0.11–0.45, FDRSMR = 0.013) was negatively correlated with the risk of IPF.ConclusionsThis study demonstrated that genetically determined plasma levels of the BTRC, RIPK4, and LINC01252 genes, as well as methylation levels of cg00045227 (OR8U8), cg00577578 (GBAP1), cg07163735 (MAPT), cg14222479 (ARPM1), and cg19263494 (PMF1), have causal influences on the risk of IPF.

Exploring Novel Genomic Loci and Candidate Genes Associated with Plant Height in Bulgarian Bread Wheat via Multi-Model GWAS.

In the context of crop breeding, plant height (PH) plays a pivotal role in determining straw and grain yield. Although extensive research has explored the genetic control of PH in wheat, there remains an opportunity for further advancements by integrating genomics with growth-related phenomics. Our study utilizes the latest genome-wide association scan (GWAS) techniques to unravel the genetic basis of temporal variation in PH across 179 Bulgarian bread wheat accessions, including landraces, tall historical, and semi-dwarf modern varieties. A GWAS was performed with phenotypic data from three growing seasons, the calculated best linear unbiased estimators, and the leveraging genotypic information from the 25K Infinium iSelect array, using three statistical methods (MLM, FarmCPU, and BLINK). Twenty-five quantitative trait loci (QTL) associated with PH were identified across fourteen chromosomes, encompassing 21 environmentally stable quantitative trait nucleotides (QTNs), and four haplotype blocks. Certain loci (17) on chromosomes 1A, 1B, 1D, 2A, 2D, 3A, 3B, 4A, 5B, 5D, and 6A remain unlinked to any known Rht (Reduced height) genes, QTL, or GWAS loci associated with PH, and represent novel regions of potential breeding significance. Notably, these loci exhibit varying effects on PH, contribute significantly to natural variance, and are expressed during seedling to reproductive stages. The haplotype block on chromosome 6A contains five QTN loci associated with reduced height and two loci promoting height. This configuration suggests a substantial impact on natural variation and holds promise for accurate marker-assisted selection. The potentially novel genomic regions harbor putative candidate gene coding for glutamine synthetase, gibberellin 2-oxidase, auxin response factor, ethylene-responsive transcription factor, and nitric oxide synthase; cell cycle-related genes, encoding cyclin, regulator of chromosome condensation (RCC1) protein, katanin p60 ATPase-containing subunit, and expansins; genes implicated in stem mechanical strength and defense mechanisms, as well as gene regulators such as transcription factors and protein kinases. These findings enrich the pool of semi-dwarfing gene resources, providing the potential to further optimize PH, improve lodging resistance, and achieve higher grain yields in bread wheat.

Inheritance and QTL mapping identified multi-effects loci for fatty acid related traits in peanut (Arachis hypogaea L.)

Peanut (Arachis hypogaea L.) is an important oil and edible protein crop. The fatty acid composition not only influences the quality of peanut oil but also impacts flavor, shelf life, and consumer health. Peanut oil comprises approximately 80% oleic acid (C18:1) and linoleic acid (C18:2), 10% palmitic acid (C16:0), and the remaining 10% includes stearic acid (C18:0), arachidic acid (C20:0), gadoleic acid (C20:1), behenic acid (C22:0), and lignoceric acid (C24:0). To unravel the genetic foundation of fatty acid content and delve into QTL localization, we utilized high-density SNP microarrays for genotyping the RIL population of ‘SunOleic 97R’ × ‘NC94022’. A genetic linkage map was constructed with 3141 SNP markers, covering a total genetic distance of 3051.81 cM. We identified 60 quantitative trait loci (QTLs) associated with fatty acids which distributed in 11 linkage group, with phenotypic variance explained (PVE) ranging from 1.37% to 44.92%. Notably, the QTL qFAT_A05.1 and qFAT_A08.1 are multiple-effect loci contributing to various fatty acid compositions. Moreover, we identified 15 haplotypes for the QTL qFAT_A05.1 and qFAT_A08.1 through genotyping 178 peanut germplasms. Haplotypes analysis in natural population confirmed the closely relationship of the QTLs with the content of oil, oleic acid, lignoceric acid, palmitic acid and behenic acid. This study serves as a valuable reference for selecting improved peanut genotypes with superior oil quality and desirable fatty acid composition.

Construction of a high-density genetic map and QTL localization of body weight and wool production related traits in Alpine Merino sheep based on WGR

BackgroundThe Alpine Merino is a new breed of fine-wool sheep adapted to the cold and arid climate of the plateau in the world. It has been popularized in Northwest China due to its superior adaptability as well as excellent production performance. Those traits related to body weight, wool yield, and wool fiber characteristics, which are economically essential traits in Alpine Merino sheep, are controlled by QTL (Quantitative Trait Loci). Therefore, the identification of QTL and genetic markers for these key economic traits is a critical step in establishing a MAS (Marker-Assisted Selection) breeding program.ResultsIn this study, we constructed the high-density genetic linkage map of Alpine Merino sheep by sequencing 110 F1 generation individuals using WGR (Whole Genome Resequencing) technology. 14,942 SNPs (Single Nucleotide Polymorphism) were identified and genotyped. The map spanned 2,697.86 cM, with an average genetic marker interval of 1.44 cM. A total of 1,871 high-quality SNP markers were distributed across 27 linkage groups, with an average of 69 markers per LG (Linkage Group). Among them, the smallest genetic distance is 19.62 cM for LG2, while the largest is 237.19 cM for LG19. The average genetic distance between markers in LGs ranged from 0.24 cM (LG2) to 3.57 cM (LG17). The marker density in the LGs ranged from LG14 (39 markers) to LG1 (150 markers).ConclusionsThe first genetic map of Alpine Merino sheep we constructed included 14,942 SNPs, while 46 QTLs associated with body weight, wool yield and wool fiber traits were identified, laying the foundation for genetic studies and molecular marker-assisted breeding. Notably, there were QTL intervals for overlapping traits on LG4 and LG8, providing potential opportunities for multi-trait co-breeding and further theoretical support for selection and breeding of ultra-fine and meaty Alpine Merino sheep.

QTL identified that influence tuber length-width ratio, degree of flatness, tuber size, and specific gravity in a russet-skinned, tetraploid mapping population.

Potato tuber shape, size, and specific gravity are important agronomic traits in the russet market class of potatoes with an impact on quality, consistency, and product recovery of processed foods such as French fries. Therefore, identifying genetic regions associated with the three traits through quantitative trait locus/loci (QTL) analysis is a crucial process in the subsequent development of marker-assisted selection for use in potato breeding programs. QTL analysis was conducted on a tetraploid mapping population consisting of 190 individuals derived from the cross between two russet-skinned parents, Palisade Russet and the breeding clone ND028673B-2Russ. Field data collected over a 2-year period and used in the QTL analyses included tuber length-width and width-depth ratios that were obtained using a digital caliper. The width-depth ratio provided an assessment of the "flatness" of a tuber, which is of importance in potato processing. To cross-validate the accuracy and differences among tuber shape measurement methods, a trained evaluator also assessed the identical tubers based on 1-5 scale (compressed to long) visual assessment method. Furthermore, the weights of analyzed tubers and specific gravities were also collected during the phenotyping process for each mapping clone. A major tuber shape QTL was consistently observed on chromosome 10 with both the length-width ratio and visual assessments. On chromosome 4, a significant QTL for tuber shape from the visual assessment phenotypic data was also detected. Additionally, a tuber shape-related QTL on chromosome 6 was also detected from the length-width ratio data from 2020. Chromosome 2 was also identified as having a significant QTL for the width-depth ratio, which is of importance in influencing the flatness of a tuber. One significant QTL for tuber weight (i.e., tuber size) was observed on chromosome 5, and a significant QTL for specific gravity was found on chromosome 3. These significant and major QTL should be useful for developing marker-assisted selection for more efficient potato breeding.

Abstract 114: Identification of the actionable target, LILRB4, through genetic linkage analysis of Diversity Outbred (DO) F1 mice expressing HER2(neu)

Abstract Our goal is to identify, in situ, the regulatory genes that dictate the onset age and growth rate of spontaneously arising tumors to implement new intervention strategies. For genetic linkage analysis, we crossed HER2(neu) Tg mice with Diversity Outbred (DO) mice, an outbred population comprised of 8 founding strains (A/J, C57BL/6J, 129S1/SvlmJ, NOD/ShiLtJ, NZO/HILtJ, CAST/EiJ, PWK/PhJ, WSB/EiJ) maintained by non-sibling crossing to ensure each mouse is genetically unique. Using R/QTL package, we linked Quantitative Trait Loci (QTL) in Chr 1 and X with tumor onset age, and a Chr 10 QTL with tumor growth rate. The Chr1 (=human Chr2) QTL was linked to human breast cancer diagnosis in 11 Genome-Wide Association Studies (GWAS; the human GWAS catalog, https://www.ebi.ac.uk/gwas/). Because human GWAS data is deficient in Chr X mapping and also does not assess tumor growth rate as a trait, the QTL loci identified in mouse Chr X and 10 were discoveries beyond the capacity of human GWAS. In total, we identified 26 candidate genes across the 3 QTL. For clinical validation, the genes were analyzed with CodeAI (Caris LS) which associated cancer patient clinical data with candidate gene expression. We found 21/26 genes significantly associated with the survival of patients with primary (n=3,533) and/or metastatic (n=4,870) breast cancers and 17/26 were associated with lung cancer (n=11,334) survival, with 13 overlapping genes between lung and breast cancer, indicating broad applicability of these candidate genes. We interrogated the immune status in BALB NeuT and (BALBxPWK)F1 NeuT mice because the F1 mice developed tumors around 9 wk, much earlier than the 14 wk observed in BALB NeuT mice. Surprisingly, (BALBxPWK)F1 mice responded to cancer vaccines more vigorously. Single cell RNA (scRNA) libraries from (BALBxPWK)F1 NeuT tumors showed an expanded lymphocyte cluster (12%), compared with BALB NeuT (2%) and an enrichment of T cell activation genes. These findings may reflect a deficiency in tumor cell recognition by the activated anti-tumor effectors and a window of opportunity for correction. Of the 21 candidate genes, LILRB4, a myeloid cell checkpoint molecule, was of particular interest. Expression of LILRB4 is predictive of patient survival in both breast and lung cancer. Using scRNA sequencing, we found this transmembrane receptor expressed primarily by tumor infiltrating myeloid cells. In a reported scRNA sequencing dataset (GSE161529), LILRB4 was expressed by infiltrating macrophages in human breast cancers, and is also correlated with reduced survival. In a PAN Cancer ATACseq dataset (Corces et al., 2018), promoter accessibility of LILRB4 was associated with reduced survival. Taken together, there are multiple immune regulatory mechanisms of tumor progression and LILRB4 is an important new actionable target. CA76340 (WZW), KCI TBM program (JBJ) and CCSG P30 CA022453 (GB). Citation Format: Jennifer B. Jacob, Wei-Zen Wei, Benjamin L. Kidder, Tolulope Adeyelu, Andrew Elliott, Gerold Bepler, Joyce D. Reyes. Identification of the actionable target, LILRB4, through genetic linkage analysis of Diversity Outbred (DO) F1 mice expressing HER2(neu) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 114.

Mapping crown rust resistance in the oat diploid accession PI 258731 (Avena strigosa).

Oat crown rust, caused by Puccinia coronata Corda f. sp. avenae Eriks. (Pca), is a major biotic impediment to global oat production. Crown rust resistance has been described in oat diploid species A. strigosa accession PI 258731 and resistance from this accession has been successfully introgressed into hexaploid A. sativa germplasm. The current study focuses on 1) mapping the location of QTL containing resistance and evaluating the number of quantitative trait loci (QTL) conditioning resistance in PI 258731; 2) understanding the relationship between the original genomic location in A. strigosa and the location of the introgression in the A. sativa genome; 3) identifying molecular markers tightly linked with PI 258731 resistance loci that could be used for marker assisted selection and detection of this resistance in diverse A. strigosa accessions. To achieve this, A. strigosa accessions, PI 258731 and PI 573582 were crossed to produce 168 F5:6 recombinant inbred lines (RILs) through single seed descent. Parents and RILs were genotyped with the 6K Illumina SNP array which generated 168 segregating SNPs. Seedling reactions to two isolates of Pca (races TTTG, QTRG) were conditioned by two genes (0.6 cM apart) in this population. Linkage mapping placed these two resistant loci to 7.7 (QTRG) to 8 (TTTG) cM region on LG7. Field reaction data was used for QTL analysis and the results of interval mapping (MIM) revealed a major QTL (QPc.FD-AS-AA4) for field resistance. SNP marker assays were developed and tested in 125 diverse A. strigosa accessions that were rated for crown rust resistance in Baton Rouge, LA and Gainesville, FL and as seedlings against races TTTG and QTRG. Our data proposed SNP marker GMI_ES17_c6425_188 as a candidate for use in marker-assisted selection, in addition to the marker GMI_ES02_c37788_255 suggested by Rine's group, which provides an additional tool in facilitating the utilization of this gene in oat breeding programs.

High-throughput phenotyping and deep learning to analyze dynamic panicle growth and dissect the genetic architecture of yield formation

The dynamic growth of shoots and panicles determines the final agronomic traits and yield. However, it is difficult to quantify such dynamics manually for large populations. In this study, based on the high-throughput rice automatic phenotyping platform and deep learning, we developed a novel image analysis pipeline (Panicle-iAnalyzer) to extract image-based traits (i-traits) including 52 panicle and 35 shoot i-traits and tested the system using a recombinant inbred line population derived from a cross between Zhenshan 97 and Minghui 63. At the maturity stage, image recognition using a deep learning network (SegFormer) was applied to separate the panicles from the shoot in the image. Eventually, with these obtained i-traits, the yield could be well predicted, and the R2 was 0.862. Quantitative trait loci (QTL) mapping was performed using an extra-high density single nucleotide polymorphism (SNP) bin map. A total of 3,586 time-specific QTLs were identified for the traits and parameters at various time points. Many of the QTLs were repeatedly detected at different time points. We identified the presence of cloned genes, such as TAC1, Ghd7.1, Ghd7, and Hd1, at QTL hotspots and evaluated the magnitude of their effects at different developmental stages. Additionally, this study identified numerous new QTL loci worthy of further investigation.

Identification of QTL associated with plant vine characteristics and infection response to late blight, early blight, and Verticillium wilt in a tetraploid potato population derived from late blight-resistant Palisade Russet.

Potato late blight (causal agent Phytophthora infestans) is a disease of potatoes with economic importance worldwide. Control is primarily through field monitoring and the application of fungicides. Control of late blight with fungicides and host plant resistance is difficult, with documented cases of such control measures failing with the advent of new pathotypes of P. infestans. To better understand host plant resistance and to develop more durable late blight resistance, Quantitative Trait Locus/Loci (QTL) analysis was conducted on a tetraploid mapping population derived from late blight-resistant potato cultivar Palisade Russet. Additionally, QTL analyses for other traits such as Verticillium wilt and early blight resistance, vine size and maturity were performed to identify a potential relationship between multiple traits and prepare genetic resources for molecular markers useful in breeding programs. For this, one hundred ninety progenies from intercrossing Palisade Russet with a late blight susceptible breeding clone (ND028673B-2Russ) were assessed. Two parents and progenies were evaluated over a two-year period for response to infection by the US-8 genotype of P. infestans in inoculated field screenings in Corvallis, Oregon. In Aberdeen, Idaho, the same mapping population was also evaluated for phenotypic response to early blight and Verticillium wilt, and vine size and maturity in a field over a two-year period. After conducting QTL analyses with those collected phenotype data, it was observed that chromosome 5 has a significant QTL for all five traits. Verticillium wilt and vine maturity QTL were also observed on chromosome 1, and vine size QTL was also found on chromosomes 3 and 10. An early blight QTL was also detected on chromosome 2. The QTL identified in this study have the potential for converting into breeder-friendly molecular markers for marker-assisted selection.

Improved Genetic Map and Localization of Quantitative Trait Loci for Quality Traits in Auricularia heimuer

Auricularia heimuer is among China’s most important edible mushrooms and is rich in gum. With the improvement of people’s quality of life, demand is increasing for high-quality and good-tasting food; thus, the texture of A. heimuer is the focus of increasing attention. In this study, we added extra markers to a previously constructed genetic linkage map to generate a high-density genetic linkage map of A. heimuer, resolved the attributes of substrate quality-related traits, and performed quantitative trait locus (QTL) localization. The original genetic linkage map was improved by adding two new linkage groups, merging seven linkage groups into three linkage groups, and increasing the average linkage distance and total linkage estimated length. We anchored the 142 scaffolds of the genome to the improved genetic linkage map. In total, 15 significant QTLs controlling four quality-related traits were detected. Gumminess and chewiness, and cohesiveness and resilience, were linked. Three genes controlled cohesiveness and resilience; one gene controlled gumminess and chewiness. In conclusion, this study lays the foundation for gene localization and chromosome assembly in A. heimuer, elucidation of the mechanism of substrate quality-related trait formation, and provides a basis for precision breeding of A. heimuer.

Genetics of behavioural evolution in giant mice from Gough Island.

The evolution of behaviour on islands is a pervasive phenomenon that contributed to Darwin's theory of natural selection. Island populations frequently show increased boldness and exploration compared with their mainland counterparts. Despite the generality of this pattern, the genetic basis of island-associated behaviours remains a mystery. To address this gap in knowledge, we genetically dissected behaviour in 613 F2s generated by crossing inbred mouse strains from Gough Island (where they live without predators or human commensals) and a mainland conspecific. We used open field and light/dark box tests to measure seven behaviours related to boldness and exploration in juveniles and adults. Across all assays, we identified a total of 41 quantitative trait loci (QTL) influencing boldness and exploration. QTL have moderate effects and are often unique to specific behaviours or ages. Function-valued trait mapping revealed changes in estimated effects of QTL during assays, providing a rare dynamic window into the genetics of behaviour often missed by standard approaches. The genomic locations of QTL are distinct from those found in laboratory strains of mice, indicating different genetic paths to the evolution of similar behaviours. We combine our mapping results with extensive phenotypic and genetic information available for laboratory mice to nominate candidate genes for the evolution of behaviour on islands.

Novel QTL for chilling tolerance at germination and early seedling stages in sorghum.

Sorghum (Sorghum bicolor L.) a drought tolerant staple crop for half a billion people in Africa and Asia, an important source of animal feed throughout the world and a biofuel feedstock of growing importanceorghum's originated from tropical regions rendering the crop to be cold sensitive. Low temperature stresses such as chilling and frost greatly affect the agronomic performance of sorghum and limit its geographical distribution, posing a major problem in temperate environments when sorghum is planted early. Understanding the genetic basis of wide adaptability and of sorghum would facilitate molecular breeding programs and studies of other C4 crops. The objective of this study is to conduct quantitative trait loci analysis using genotying by sequencing for early seed germination and seedling cold tolerance in two sorghum recombinant inbred lines populations. To accomplish that, we used two populations of recombinant inbred lines (RIL) developed from crosses between cold-tolerant (CT19, ICSV700) and cold-sensitive (TX430, M81E) parents. The derived RIL populations were evaluated for single nucleotide polymorphism (SNP) using genotype-by-sequencing (GBS) in the field and under controlled environments for their response to chilling stress. Linkage maps were constructed with 464 and 875 SNPs for the CT19 X TX430 (C1) and ICSV700 X M81 E (C2) populations respectively. Using quantitative trait loci (QTL) mapping, we identified QTL conferring tolerance to chilling tolerance at the seedling stage. A total of 16 and 39 total QTL were identified in the C1 and C2 populations, respectively. Two major QTL were identified in the C1 population, and three major QTL were mapped in the C2 population. Comparisons between the two populations and with previously identified QTL show a high degree of similarity in QTL locations. Given the amount of co-localization of QTL across traits and the direction of allelic effect supports that these regions have a pleiotropic effect. These QTL regions were also identified to be highly enriched for genes encoding chilling stress and hormonal response genes. This identified QTL can be useful in developing tools for molecular breeding of sorghums with improved low-temperature germinability.

Resistance QTLs controlling leaf and neck blast disease identified in a doubled haploid rice population

One of the biotic constraints in rice production worldwide is blast disease which can control by planting resistant varieties. To find out effective resistance, blast resistance quantitative trait loci (QTL) were mapped against 20 and 3 virulent isolates for leaf blast and neck blast, respectively, using 111 doubled haploid lines from the cross of IR64 and Azucena. QTLs associated with leaf blast were found on chromosomes 1, 2, 4, 7, 8, 10, 11, and 12 (%R2 = 3.6 – 64.3), while neck blast linked QTLs were identified on chromosomes 1, 6, 10, and 12 (%R2 = 6.4 – 22.6). The new QTLs were identified on chromosome 1; however, most QTLs were mapped in the vicinity of resistance genes in previous references. The genetic relationship of leaf and neck blast was explained by the coincidence of detected QTLs and positive value of pathogenicity correlation (r = 4.5 – 4.7). This study provides reliable QTLs locations that will benefit rice breeding programs to develop new cultivars containing durable and broad-spectrum resistance to leaf and neck blast disease.

QTL mapping and transcriptome analysis of sugar content during fruit ripening of Pyrus pyrifolia.

Sugar content is an important trait of fruits. The genetic background of fruits can affect their sugar content in different cultivars. The quantitative trait loci and genes related to sugar content during fruit ripening remain unclear. In this study, we performed quantitative trait locus (QTL) mapping of sugar content. Two QTLs (qSugar-LG6-Chr7 and qSugar-LG12-Chr3) were identified based on their total sugar contents. A total of 577 and 519 genes were annotated around these two QTL loci. The contents of fructose, sorbitol, glucose, and sucrose were measured at six time points in four cultivars before fruit maturation, including two sweet cultivars ("Zaoshengxinshui" and "ZQ65") and two general cultivars ("Qiushui" and "ZQ82"). In sweet cultivars, sucrose and fructose accumulate substantially, and sorbitol content decreases significantly during fruit ripening. A transcriptome analysis identified 125 upregulated and 222 downregulated differentially expressed genes (DEGs) in sweet cultivars. Two sucrose transport genes (PpSUT, LOC103964096, and LOC103940043) were negatively correlated with sugar content. A weighted gene co-expression network analysis showed that two genes, sorbitol dehydrogenase (PpSDH, LOC103960512 and LOC103960513), around the locus of qSugar-LG6-Chr7 were negatively co-expressed with the total sugar content, which was downregulated in the sweet cultivars. PpSDH and PpSUT may play important roles in regulating sugar content during pear ripening. Transcriptome analysis also revealed that some DEGs were related to sugars (PpS6PDH and ATP-PpPFK), hormones (PpARG7), and transcription factors (PpEMB1444, PpCYP734A1, and PpWRKY50). In conclusion, this study provides new insights into the molecular mechanisms associated with sugar content in the fruit ripening of Pyrus pyrifolia.

Identification and Pyramiding Major QTL Loci for Simultaneously Enhancing Aflatoxin Resistance and Yield Components in Peanut.

Peanut is susceptible to Aspergillus flavus infection, and the consequent aflatoxin contamination has been recognized as an important risk factor affecting food safety and industry development. Planting peanut varieties with resistance to aflatoxin contamination is regarded as an ideal approach to decrease the risk in food safety, but most of the available resistant varieties have not been extensively used in production because of their low yield potential mostly due to possessing small pods and seeds. Hence, it is highly necessary to integrate resistance to aflatoxin and large seed weight. In this study, an RIL population derived from a cross between Zhonghua 16 with high yield and J 11 with resistance to infection of A. flavus and aflatoxin production, was used to identify quantitative trait locus (QTL) for aflatoxin production (AP) resistance and hundred-seed weight (HSW). From combined analysis using a high-density genetic linkage map constructed, 11 QTLs for AP resistance with 4.61-11.42% phenotypic variation explanation (PVE) and six QTLs for HSW with 3.20-28.48% PVE were identified, including three major QTLs for AP resistance (qAFTA05.1, qAFTB05.2 and qAFTB06.3) and three for HSW (qHSWA05, qHSWA08 and qHSWB06). In addition, qAFTA05.1, qAFTB06.3, qHSWA05, qHSWA08 and qHSWB06 were detected in multiple environments. The aflatoxin contents under artificial inoculation were decreased by 34.77-47.67% in those segregated lines harboring qAFTA05.1, qAFTB05.2 and qAFTB06.3, while the HSWs were increased by 47.56-49.46 g in other lines harboring qHSWA05, qHSWA08 and qHSWB06. Conditional QTL mapping indicated that HSW and percent seed infection index (PSII) had no significant influence on aflatoxin content. Interestingly, the QT 1059 simultaneously harboring alleles of aflatoxin content including qAFTA05.1 and qAFTB05.2, alleles of PSII including qPSIIB03.1, qPSIIB03.2, and qPSIIB10 and alleles of HSW including qHSWA05, qHSWB06, qHSWA08 had better resistance to A. flavus infection and to toxin production and higher yield potential compared with the two parents of the RIL. The above identified major loci for AP resistance and HWS would be helpful for marker-assisted selection in peanut breeding.

Genome-wide association mapping for pre-harvest sprouting in European winter wheat detects novel resistance QTL, pleiotropic effects, and structural variation in multiple genomes.

Pre-harvest sprouting (PHS), germination of seeds before harvest, is a major problem in global wheat (Triticum aestivum L.) production, and leads to reduced bread-making quality in affected grain. Breeding for PHS resistance can prevent losses under adverse conditions. Selecting resistant lines in years lacking pre-harvest rain, requires challenging of plants in the field or in the laboratory or using genetic markers. Despite the availability of a wheat reference and pan-genome, linking markers, genes, allelic, and structural variation, a complete understanding of the mechanisms underlying various sources of PHS resistance is still lacking. Therefore, we challenged a population of European wheat varieties and breeding lines with PHS conditions and phenotyped them for PHS traits, grain quality, phenological and agronomic traits to conduct genome-wide association mapping. Furthermore, we compared these marker-trait associations to previously reported PHS loci and evaluated their usefulness for breeding. We found markers associated with PHS on all chromosomes, with strong evidence for novel quantitative trait locus/loci (QTL) on chromosome 1A and 5B. The QTL on chromosome 1A lacks pleiotropic effect, for the QTL on 5B we detected pleiotropic effects on phenology and grain quality. Multiple peaks on chromosome 4A co-located with the major resistance locus Phs-A1, for which two causal genes, TaPM19 and TaMKK3, have been proposed. Mapping markers and genes to the pan-genome and chromosomal alignments provide evidence for structural variation around this major PHS-resistance locus. Although PHS is controlled by many loci distributed across the wheat genome, Phs-A1 on chromosome 4A seems to be the most effective and widely deployed source of resistance, in European wheat varieties.

Integrating top-down and bottom-up approaches to understand the genetic architecture of speciation across a monkeyflower hybrid zone.

Understanding the phenotypic and genetic architecture of reproductive isolation is a long-standing goal of speciation research. In several systems, large-effect loci contributing to barrier phenotypes have been characterized, but such causal connections are rarely known for more complex genetic architectures. In this study, we combine "top-down" and "bottom-up" approaches with demographic modelling toward an integrated understanding of speciation across a monkeyflower hybrid zone. Previous work suggests that pollinator visitation acts as a primary barrier to gene flow between two divergent red- and yellow-flowered ecotypes of Mimulus aurantiacus. Several candidate isolating traits and anonymous single nucleotide polymorphism loci under divergent selection have been identified, but their genomic positions remain unknown. Here, we report findings from demographic analyses that indicate this hybrid zone formed by secondary contact, but that subsequent gene flow was restricted by widespread barrier loci across the genome. Using a novel, geographic cline-based genome scan, we demonstrate that candidate barrier loci are broadly distributed across the genome, rather than mapping to one or a few "islands of speciation." Quantitative trait locus (QTL) mapping reveals that most floral traits are highly polygenic, with little evidence that QTL colocalize, indicating that most traits are genetically independent. Finally, we find little evidence that QTL and candidate barrier loci overlap, suggesting that some loci contribute to other forms of reproductive isolation. Our findings highlight the challenges of understanding the genetic architecture of reproductive isolation and reveal that barriers to gene flow other than pollinator isolation may play an important role in this system.

Identification and characterization of stable QTLs for vascular bundle number at the panicle neck in rice (Oryza sativa L.).

A large vascular bundle number (VBN) in the panicle neck in rice (Oryza sativa L.) is related to the ability to transport assimilates from stem and leaf to reproductive organs during seed maturation. Several quantitative trait loci (QTLs) for VBN have been identified by using segregating populations derived from a cross between indica and japonica rice cultivars. However, the detailed location, effect, and interaction of QTLs for VBN were not understood well. Here, to elucidate the genetic basis of VBN, we identified three stable QTLs for VBN-qVBN5, qVBN6 and qVBN11-by using 71 recombinant inbred lines derived from a cross between indica 'IR24' and japonica 'Asominori'. We confirmed their positions and characterized their effects by using chromosome segment substitution lines (CSSLs) with an 'IR24' genetic background. qVBN6 had the most substantial effect on VBN, followed by qVBN11 and qVBN5. We developed pyramided lines carrying two QTLs for VBN to estimate their interaction. The combination of qVBN6 and qVBN11 accumulated VBN negatively in the pyramided lines owing to the independent actions of each QTL. The QTLs detected for VBN will enhance our understanding of genetic mechanisms of VBN and can be used in rice breeding.

Quantitative trait locus mapping for important yield traits of a sorghum-sudangrass hybrid using a high-density single nucleotide polymorphism map.

The sorghum-sudangrass hybrid is a vital gramineous herbage.The F2 population was obtained to clarify genetic regularities among the traits of sorghum-sudangrass hybrids by bagging and selfing in the F1 generation using 'scattered ear sorghum' and 'red hull sudangrass.' This hybrid combines the characteristics of the strong resistance of parents, high yield, and good palatability and has clear heterosis. A thorough understanding of the genetic mechanisms of yield traits in sorghum-sudangrass hybrids is essential in improving their yield. Therefore, we conducted quantitative trait locus (QTL) mapping for plant height, stem diameter, tiller number, leaf number, leaf length, leaf width, and fresh weight of each plant in three different environments, using a high-density genetic linkage map based on single nucleotide polymorphism markers previously constructed by our team. A total of 55 QTLs were detected, uniformly distributed over the 10 linkage groups (LGs), with logarithm of odds values ranging between 2.5 and 7.1, which could explain the 4.9-52.44% phenotypic variation. Furthermore, 17 yield-related relatively high-frequency QTL (RHF-QTL) loci were repeatedly detected in at least two environments, with an explanatory phenotypic variation of 4.9-30.97%. No RHF-QTLs were associated with the tiller number. The genes within the confidence interval of RHF-QTL were annotated, and seven candidate genes related to yield traits were screened. Three QTL sites overlapping or adjacent to previous studies were detected by comparative analysis. We also found that QTL was enriched and that qLL-10-1 and qFW-10-4 were located at the same location of 25.81 cM on LG10. The results of this study provide a foundation for QTL fine mapping, candidate gene cloning, and molecular marker-assisted breeding of sorghum-sudangrass hybrids.

Mining candidate genes of grape berry cracking based on high density genetic map

Fruit cracking is a phenomenon in which the peel cracks during grape berry development, which seriously affects the yield and quality of the fruit. However, there are few studies on the mining of candidate genes related to berry cracking. In order to better understand the genetic basis of berry cracking, we used the results of previous quantitative trait locus (QTL) mapping, combined with field surveys of berry-cracking types and the berry-cracking rate, to mine candidate berry-cracking genes. The results showed that three identical QTL loci were detected in two years (2019 and 2020); and three candidate genes were annotated in the QTL interval. In mature berries, the expressions of the candidate genes were more abundant in the cracking-susceptible parent (‘Crimson Seedless’) than in the cracking-resistant parent (‘Muscat Hamburg’). Grape berry cracking is a complex trait controlled by multiple genes, mainly including genes encoding cellulose synthase–like protein H1, glucan endo-1,3-beta-glucosidase 12, and brassinosteroid insensitive 1-associated receptor kinase 1. The high expression of the candidate berry-cracking genes may promote the occurrence of berry cracking. This study helps elucidate the genetic mechanism of grape berry cracking.