A Molecular Genetic Linkage Map of Eucommia ulmoides and Quantitative Trait Loci (QTL) Analysis for Growth Traits

Eucommia ulmoides is an economically important tree species for both herbal medicine and organic chemical industry. Effort to breed varieties with improved yield and quality is limited by the lack of knowledge on the genetic basis of the traits. A genetic linkage map of E. ulmoides was constructed from a full-sib family using sequence-related amplified polymorphism, amplified fragment length polymorphism, inter-simple sequence repeat and simple sequence repeat markers. In total, 706 markers were mapped in 25 linkage groups covering 2133 cM. The genetic linkage map covered approximately 89% of the estimated E. ulmoides genome with an average of 3.1 cM between adjacent markers. The present genetic linkage map was used to identify quantitative trait loci (QTL) affecting growth-related traits. Eighteen QTLs were found to explain 12.4%–33.3% of the phenotypic variance. This genetic linkage map provides a tool for marker-assisted selection and for studies of genome in E. ulmoides.     

Fine Mapping and Functional Analysis of Major Regulatory Genes of Soluble Solids Content in Wax Gourd (Benincasa hispida)

Soluble solids content (SSC) is an important quality trait of wax gourd, but reports about its regulatory genes are scarce. In this study, the SSC regulatory gene BhSSC2.1 in wax gourd was mined via quantitative trait locus (QTL) mapping based on high-density genetic mapping containing 12 linkage groups (LG) and bulked segregant analysis (BSA)-seq. QTL mapping and BSA-seq revealed for the first time that the SSC QTL (107.658–108.176 cM) of wax gourd was on Chr2 (LG2). The interpretable phenotypic variation rate and maximum LOD were 16.033% and 6.454, respectively. The QTL interval contained 13 genes. Real-time fluorescence quantitative expression analysis, functional annotation, and sequence analysis suggested that Bch02G016960, named BhSSC2.1, was a candidate regulatory gene of the SSC in wax gourd. Functional annotation of this gene showed that it codes for a NADP-dependent malic enzyme. According to BhSSC2.1 sequence variation, an InDel marker was developed for molecular marker-assisted breeding of wax gourd. This study will lay the foundation for future studies regarding breeding and understanding genetic mechanisms of wax gourd.     

Integrative Transcriptome,Genome and Quantitative Trait Loci Resources Identify Single Nucleotide Polymorphisms in Candidate Genes for Growth Traits in Turbot

Growth traits represent a main goal in aquaculture breeding programs and may be related to adaptive variation in wild fisheries. Integrating quantitative trait loci (QTL) mapping and next generation sequencing can greatly help to identify variation in candidate genes, which can result in marker-assisted selection and better genetic structure information. Turbot is a commercially important flatfish in Europe and China, with available genomic information on QTLs and genome mapping. Muscle and liver RNA-seq from 18 individuals was carried out to obtain gene sequences and markers functionally related to growth, resulting in a total of 20,447 genes and 85,344 single nucleotide polymorphisms (SNPs). Many growth-related genes and SNPs were identified and placed in the turbot genome and genetic map to explore their co-localization with growth-QTL markers. Forty-five SNPs on growth-related genes were selected based on QTL co-localization and relevant function for growth traits. Forty-three SNPs were technically feasible and validated in a wild Atlantic population, where 91% were polymorphic. The integration of functional and structural genomic resources in turbot provides a practical approach for QTL mining in this species. Validated SNPs represent a useful set of growth-related gene markers for future association, functional and population studies in this flatfish species.     

QTL Mapping and Diurnal Transcriptome Analysis Identify Candidate Genes Regulating Brassica napus Flowering Time

Timely flowering is important for seed formation and maximization of rapeseed (Brassica napus) yield. Here, we performed flowering-time quantitative trait loci (QTL) mapping using a double haploid (DH) population grown in three environments to study the genetic architecture. Brassica 60 K Illumina Infinium™ single nucleotide polymorphism (SNP) array and simple sequence repeat (SSR) markers were used for genotyping of the DH population, and a high-density genetic linkage map was constructed. QTL analysis of flowering time from the three environments revealed five consensus QTLs, including two major QTLs. A major QTL located on chromosome A03 was detected specifically in the semi-winter rapeseed growing region, and the one on chromosome C08 was detected in all environments. Ribonucleic acid sequencing (RNA-seq) was performed on the parents’ leaves at seven time-points in a day to determine differentially expressed genes (DEGs). The biological processes and pathways with significant enrichment of DEGs were obtained. The DEGs in the QTL intervals were analyzed, and four flowering time-related candidate genes were found. These results lay a foundation for the genetic regulation of rapeseed flowering time and create a rapeseed gene expression library for seven time-points in a day.     

Discovery of Genomic Regions and Candidate Genes Controlling Root Development Using a Recombinant Inbred Line Population in Rapeseed (Brassica napus L.)

Marker-assisted selection enables breeders to quickly select excellent root architectural variations, which play an essential role in plant productivity. Here, ten root-related and shoot biomass traits of a new F₆ recombinant inbred line (RIL) population were investigated under hydroponics and resulted in high heritabilities from 0.61 to 0.83. A high-density linkage map of the RIL population was constructed using a Brassica napus 50k Illumina single nucleotide polymorphism (SNP) array. A total of 86 quantitative trait loci (QTLs) explaining 4.16–14.1% of the phenotypic variances were detected and integrated into eight stable QTL clusters, which were repeatedly detected in different experiments. The codominant markers were developed to be tightly linked with three major QTL clusters, qcA09-2, qcC08-2, and qcC08-3, which controlled both root-related and shoot biomass traits and had phenotypic contributions greater than 10%. Among these, qcA09-2, renamed RT.A09, was further fine-mapped to a 129-kb interval with 19 annotated genes in the B. napus reference genome. By integrating the results of real-time PCR and comparative sequencing, five genes with expression differences and/or amino acid differences were identified as important candidate genes for RT.A09. Our findings laid the foundation for revealing the molecular mechanism of root development and developed valuable markers for root genetic improvement in rapeseed.     

Introduction and overview. Statistical methods in genetic epidemiology

Common terms used in genetics with multiple meanings are explained and a brief overview given of the four major areas of genetic epidemiology--the study of familial aggregation, segregation, cosegregation and association. Familial aggregation measures the potential for a trait to have a genetic aetiology. Segregation analysis uncovers single gene segregation. Cosegregation with genetic markers gives rise to linkage, which is used to locate trait genes on the genome. Association analysis is used for fine mapping, but rests on the assumption that linkage disequilibrium exists.     

Quantitative Trait Locus Mapping of Marsh Spot Disease Resistance in Cranberry Common Bean (Phaseolus vulgaris L.)

Common bean (Phaseolus vulgaris L.) is a food crop that is an important source of dietary proteins and carbohydrates. Marsh spot is a physiological disorder that diminishes seed quality in beans. Prior research suggested that this disease is likely caused by manganese (Mn) deficiency during seed development and that marsh spot resistance is controlled by at least four genes. In this study, genetic mapping was performed to identify quantitative trait loci (QTL) and the potential candidate genes associated with marsh spot resistance. All 138 recombinant inbred lines (RILs) from a bi-parental population were evaluated for marsh spot resistance during five years from 2015 to 2019 in sandy and heavy clay soils in Morden, Manitoba, Canada. The RILs were sequenced using a genotyping by sequencing approach. A total of 52,676 single nucleotide polymorphisms (SNPs) were identified and filtered to generate a high-quality set of 2066 SNPs for QTL mapping. A genetic map based on 1273 SNP markers distributed on 11 chromosomes and covering 1599 cm was constructed. A total of 12 stable and 4 environment-specific QTL were identified using additive effect models, and an additional two epistatic QTL interacting with two of the 16 QTL were identified using an epistasis model. Genome-wide scans of the candidate genes identified 13 metal transport-related candidate genes co-locating within six QTL regions. In particular, two QTL (QTL.3.1 and QTL.3.2) with the highest R² values (21.8% and 24.5%, respectively) harbored several metal transport genes Phvul.003G086300, Phvul.003G092500, Phvul.003G104900, Phvul.003G099700, and Phvul.003G108900 in a large genomic region of 16.8–27.5 Mb on chromosome 3. These results advance the current understanding of the genetic mechanisms of marsh spot resistance in cranberry common bean and provide new genomic resources for use in genomics-assisted breeding and for candidate gene isolation and functional characterization.     

A Quantitative Genetic Study of Sclerotinia Head Rot Resistance Introgressed from the Wild Perennial Helianthus maximiliani into Cultivated Sunflower (Helianthus annuus L.)

Sclerotinia head rot (HR), caused by Sclerotinia sclerotiorum, is an economically important disease of sunflower with known detrimental effects on yield and quality in humid climates worldwide. The objective of this study was to gain insight into the genetic architecture of HR resistance from a sunflower line HR21 harboring HR resistance introgressed from the wild perennial Helianthus maximiliani. An F₂ population derived from the cross of HA 234 (susceptible-line)/HR21 (resistant-line) was evaluated for HR resistance at two locations during 2019–2020. Highly significant genetic variations (p < 0.001) were observed for HR disease incidence (DI) and disease severity (DS) in both individual and combined analyses. Broad sense heritability (H²) estimates across environments for DI and DS were 0.51 and 0.62, respectively. A high-density genetic map of 1420.287 cM was constructed with 6315 SNP/InDel markers developed using genotype-by-sequencing technology. A total of 16 genomic regions on eight sunflower chromosomes, 1, 2, 10, 12, 13, 14, 16 and 17 were associated with HR resistance, each explaining between 3.97 to 16.67% of the phenotypic variance for HR resistance. Eleven of these QTL had resistance alleles from the HR21 parent. Molecular markers flanking the QTL will facilitate marker-assisted selection breeding for HR resistance in sunflower.     

High throughput mining and characterization of microsatellites from common carp genome

In order to supply sufficient microsatellite loci for high-density linkage mapping, whole genome shotgun (WGS) sequences of the common carp (Cyprinus carpio) were assembled and surveyed for microsatellite identification. A total of 79,014 microsatellites were collected which were harbored in 68,827 distinct contig sequences. These microsatellites were characterized in the common carp genome. Information of all microsatellites, including previously published BAC-based microsatellites, was then stored in a MySQL database, and a web-based database interface (http://genomics.cafs.ac.cn/ssrdb) was built for public access and download. A total of 3,110 microsatellites, including 1,845 from WGS and 1,265 from BAC end sequences (BES), were tested and genotyped on a mapping family with 192 individuals. A total of 963 microsatellites markers were validated with polymorphism in the mapping family. They will soon be used for high-density linkage mapping with a vast number of polymorphic SNP markers.     

Development and Validation of SNP and InDel Markers for Pod-Shattering Tolerance in Soybean

Pod-shattering causes a significant yield loss in many soybean cultivars. Shattering-tolerant cultivars provide the most effective approach to minimizing this loss. We developed molecular markers for pod-shattering and validated them in soybeans with diverse genetic backgrounds. The genes Glyma.16g141200, Glyma.16g141500, and Glyma.16g076600, identified in our previous study by quantitative trait locus (QTL) mapping and whole-genome resequencing, were selected for marker development. The whole-genome resequencing of three parental lines (one shattering-tolerant and two shattering-susceptible) identified single nucleotide polymorphism (SNP) and/or insertion/deletion (InDel) regions within or near the selected genes. Two SNPs and one InDel were converted to Kompetitive Allele-Specific PCR (KASP) and InDel markers, respectively. The accuracy of the markers was examined in the two recombinant inbred line populations used for the QTL mapping, as well as the 120 varieties and elite lines, through allelic discrimination and phenotyping by the oven-drying method. Both types of markers successfully discriminated the pod shattering-tolerant and shattering-susceptible genotypes. The prediction accuracy, which was as high as 90.9% for the RILs and was 100% for the varieties and elite lines, also supported the accuracy and usefulness of these markers. Thus, the markers can be used effectively for genetic and genomic studies and the marker-assisted selection for pod-shattering tolerance in soybean.     

Identification of a Major QTL and Validation of Related Genes for Tiller Angle in Rice Based on QTL Analysis

An ideal plant architecture is an important condition to achieve high crop yields. The tiller angle is an important and complex polygenic trait of rice (Oryza sativa L.) plant architecture. Therefore, the discovery and identification of tiller angle-related genes can aid in the improvement of crop architecture and yield. In the present study, 222 SSR markers were used to establish a high-density genetic map of rice doubled haploid population, and a total of 8 quantitative trait loci (QTLs) were detected based on the phenotypic data of the tiller angle and tiller crown width over 2 years. Among them, four QTLs (qTA9, qCW9, qTA9-1, and qCW9-1) were overlapped at marker interval RM6235–RM24288 on chromosome 9 with a large effect value regarded as a stable major QTL. The selected promising related genes were further identified by relative gene expression analysis, which gives us a basis for the future cloning of these genes. Finally, OsSAURq9, which belongs to the SMALL AUXIN UP RNA (SAUR), an auxin-responsive protein family, was selected as a target gene. Overall, this work will help broaden our knowledge of the genetic control of tiller angle and tiller crown width, and this study provides both a good theoretical basis and a new genetic resource for the breeding of ideal-type rice.     

Genomics-Assisted Breeding for Quantitative Disease Resistances in Small-Grain Cereals and Maize

Generating genomics-driven knowledge opens a way to accelerate the resistance breeding process by family or population mapping and genomic selection. Important prerequisites are large populations that are genomically analyzed by medium- to high-density marker arrays and extensive phenotyping across locations and years of the same populations. The latter is important to train a genomic model that is used to predict genomic estimated breeding values of phenotypically untested genotypes. After reviewing the specific features of quantitative resistances and the basic genomic techniques, the possibilities for genomics-assisted breeding are evaluated for six pathosystems with hemi-biotrophic fungi: Small-grain cereals/Fusarium head blight (FHB), wheat/Septoria tritici blotch (STB) and Septoria nodorum blotch (SNB), maize/Gibberella ear rot (GER) and Fusarium ear rot (FER), maize/Northern corn leaf blight (NCLB). Typically, all quantitative disease resistances are caused by hundreds of QTL scattered across the whole genome, but often available in hotspots as exemplified for NCLB resistance in maize. Because all crops are suffering from many diseases, multi-disease resistance (MDR) is an attractive aim that can be selected by specific MDR QTL. Finally, the integration of genomic data in the breeding process for introgression of genetic resources and for the improvement within elite materials is discussed.     

Genes Associated with Foliar Resistance to Septoria Nodorum Blotch of Hexaploid Wheat (Triticum aestivum L.)

The genetic control of host response to the fungal necrotrophic disease Septoria nodorum blotch (SNB) in bread wheat is complex, involving many minor genes. Quantitative trait loci (QTL) controlling SNB response were previously identified on chromosomes 1BS and 5BL. The aim of this study, therefore, was to align and compare the genetic map representing QTL interval on 1BS and 5BS with the reference sequence of wheat and identify resistance genes (R-genes) associated with SNB response. Alignment of QTL intervals identified significant genome rearrangements on 1BS between parents of the DH population EGA Blanco, Millewa and the reference sequence of Chinese Spring with subtle rearrangements on 5BL. Nevertheless, annotation of genomic intervals in the reference sequence were able to identify and map 13 and 12 R-genes on 1BS and 5BL, respectively. R-genes discriminated co-located QTL on 1BS into two distinct but linked loci. NRC1a and TFIID mapped in one QTL on 1BS whereas RGA and Snn1 mapped in the linked locus and all were associated with SNB resistance but in one environment only. Similarly, Tsn1 and WK35 were mapped in one QTL on 5BL with NETWORKED 1A and RGA genes mapped in the linked QTL interval. This study provided new insights on possible biochemical, cellular and molecular mechanisms responding to SNB infection in different environments and also addressed limitations of using the reference sequence to identify the full complement of functional R-genes in modern varieties.     

Identification and Fine Mapping of a Locus Related to Leaf Up-Curling Trait (Bnuc3) in Brassica napus

Leaf trait is an important target trait in crop breeding programs. Moderate leaf curling may be a help for improving crop yield by minimizing the shadowing by leaves. Mining locus for leaf curling trait is of significance for plant genetics and breeding researches. The present study identified a novel rapeseed accession with up-curling leaf, analyzed the up-curling leaf trait inheritance, and fine mapped the locus for up-curling leaf property (Bnuc3) in Brassica napus. Genetic analysis revealed that the up-curling leaf trait is controlled by a single dominant locus, named BnUC3. We performed an association study of BnUC3 with single nucleotide polymorphism (SNP) markers using a backcross population derived from the homozygous up-curling leaf line NJAU-M1295 and the canola variety ‘zhongshuang11’ with typical flat leaves, and mapped the BnUC3 locus in a 1.92 Mb interval of chromosome A02 of B. napus. To further map BnUC3, 232 simple sequence repeat (SSR) primers and four pairs of Insertion/Deletion (InDel) primers were developed for the mapping interval. Among them, five SSR markers and two InDel markers were polymorphic. By these markers, the mapping interval was narrowed to 92.0 kb using another F₂ population. This fine mapping interval has 11 annotated genes among which BnaA02T0157000ZS were inferred to be candidate casual genes for up-curling leaf based on the cloned sequence analysis, gene functionality, and gene expression analysis. The current study laid a foundational basis for further elucidating the mechanism of BnUC3 and breeding of variety with up-curling leaf.     

Molecular mapping and identification of soybean fatty acid modifier quantitative trait loci

Altering FA content in soybean [Glycine max (L.) Merr.] oil for improved functionality is a research goal of many soybean breeders. Several of the genes that alter palmitic, stearic, oleic, linoleic, and linolenic acids are modifier genes with small effects, causing these FA traits to act as quantitative traits. The objective of this study was to identify modifier FA quantitative trait loci (QTL) in soybean. A recombinant inbred line population was created from two prominent ancestors of currently available U.S. cultivars (Essex and Williams) and grown in five environments. One hundred simple sequence repeat markers spaced throughout the genome were mapped in this population. QTL were found for all five FA traits on the soybean linkage groups C2, D2, D1b, F, K, and L. A single marker interval on linkage group L contained the largest QTL for palmitic (r ²=13.1%), oleic (r ²=35.3%), linoleic (r ²=50.5%), and linolenic acids (r ²=24.8%); however, this interval also contained the gene for growth habit (Dt1) and was significantly associated with maturity. Other modifier QTL found in this study may be of use in marker-assisted selection to enable breeders to increase genetic gains for desirable FA composition of soybean.     

Quantitative Trait Loci Mapping for Bacterial Blight Resistance in Rice Using Bulked Segregant Analysis

Oryza meyeriana is highly resistant to rice bacterial blight (BB) and this resistance trait has been transferred to cultivated rice (O. sativa) using asymmetric somatic hybridization. However, no resistance genes have yet been cloned. In the present study, a progeny of the somatic hybridization with high BB resistance was crossed with a rice cultivar with high BB susceptibility to develop an F₂ population. Using bulked segregant analysis (BSA), 17 polymorphic markers that were linked to rice BB resistance were obtained through scanning a total of 186 simple sequence repeats (SSR) and sequence-tagged site (STS) markers, evenly distributed on 12 chromosomes. A genetic linkage map was then constructed based on the 17 linkage markers and the F₂ segregating population, which was followed by mapping for quantitative trait loci (QTLs) for BB resistance. Three QTLs were identified on chromosomes 1, 3 and 5, respectively, and the alleles of the resistant parent at any of the QTLs increased BB resistance. All of the three QTLs had a strong effect on resistance, explaining about 21.5%, 12.3% and 39.2% of the resistance variance, respectively. These QTLs were different from the loci of the BB resistance genes that have been identified in previous studies. The QTLs mapped in this work will facilitate the isolation of novel BB resistance genes and their utilization in rice resistance breeding.     

Identification of Novel Genomic Regions for Bacterial Leaf Pustule (BLP) Resistance in Soybean (Glycine max L.) via Integrating Linkage Mapping and Association Analysis

Bacterial leaf pustule (BLP), caused by Xanthornonas axonopodis pv. glycines (Xag), is a worldwide disease of soybean, particularly in warm and humid regions. To date, little is known about the underlying molecular mechanisms of BLP resistance. The only single recessive resistance gene rxp has not been functionally identified yet, even though the genotypes carrying the gene have been widely used for BLP resistance breeding. Using a linkage mapping in a recombinant inbred line (RIL) population against the Xag strain Chinese C5, we identified that quantitative trait locus (QTL) qrxp–17–2 accounted for 74.33% of the total phenotypic variations. We also identified two minor QTLs, qrxp–05–1 and qrxp–17–1, that accounted for 7.26% and 22.26% of the total phenotypic variations, respectively, for the first time. Using a genome-wide association study (GWAS) in 476 cultivars of a soybean breeding germplasm population, we identified a total of 38 quantitative trait nucleotides (QTNs) on chromosomes (Chr) 5, 7, 8, 9,15, 17, 19, and 20 under artificial infection with C5, and 34 QTNs on Chr 4, 5, 6, 9, 13, 16, 17, 18, and 20 under natural morbidity condition. Taken together, three QTLs and 11 stable QTNs were detected in both linkage mapping and GWAS analysis, and located in three genomic regions with the major genomic region containing qrxp_17_2. Real-time RT-PCR analysis of the relative expression levels of five potential candidate genes in the resistant soybean cultivar W82 following Xag treatment showed that of Glyma.17G086300, which is located in qrxp–17–2, significantly increased in W82 at 24 and 72 h post-inoculation (hpi) when compared to that in the susceptible cultivar Jack. These results indicate that Glyma.17G086300 is a potential candidate gene for rxp and the QTLs and QTNs identified in this study will be useful for marker development for the breeding of Xag-resistant soybean cultivars.     

Development of an Australian Bread Wheat Nested Association Mapping Population,A New Genetic Diversity Resource for Breeding under Dry and Hot Climates

Genetic diversity, knowledge of the genetic architecture of the traits of interest and efficient means of transferring the desired genetic diversity into the relevant genetic background are prerequisites for plant breeding. Exotic germplasm is a rich source of genetic diversity; however, they harbor undesirable traits that limit their suitability for modern agriculture. Nested association mapping (NAM) populations are valuable genetic resources that enable incorporation of genetic diversity, dissection of complex traits and providing germplasm to breeding programs. We developed the OzNAM by crossing and backcrossing 73 diverse exotic parents to two Australian elite varieties Gladius and Scout. The NAM parents were genotyped using the iSelect wheat 90K Infinium SNP array, and the progeny were genotyped using a custom targeted genotyping-by-sequencing assay based on molecular inversion probes designed to target 12,179 SNPs chosen from the iSelect wheat 90K Infinium SNP array of the parents. In total, 3535 BC₁F_4:6 RILs from 125 families with 21 to 76 lines per family were genotyped and we found 4964 polymorphic and multi-allelic haplotype markers that spanned the whole genome. A subset of 530 lines from 28 families were evaluated in multi-environment trials over three years. To demonstrate the utility of the population in QTL mapping, we chose to map QTL for maturity and plant height using the RTM-GWAS approach and we identified novel and known QTL for maturity and plant height.