Genotyping-by-Sequencing Derived High-Density Linkage Map and its Application to QTL Mapping of Flag Leaf Traits in Bread Wheat

Identification of quantitative trait loci associated with nitrogen use efficiency in winter wheat

Maintaining winter wheat (Triticum aestivum L.) productivity with more efficient nitrogen (N) management will enable growers to increase profitability and reduce the negative environmental impacts associated with nitrogen loss. Wheat breeders would therefore benefit greatly from the identification and application of genetic markers associated with nitrogen use efficiency (NUE). To investigate the genetics underlying N response, two bi-parental mapping populations were developed and grown in four site-seasons under low and high N rates. The populations were derived from a cross between previously identified high NUE parents (VA05W-151 and VA09W-52) and a shared common low NUE parent, ‘Yorktown.’ The Yorktown × VA05W-151 population was comprised of 136 recombinant inbred lines while the Yorktown × VA09W-52 population was comprised of 138 doubled haploids. Phenotypic data was collected on parental lines and their progeny for 11 N-related traits and genotypes were sequenced using a genotyping-by-sequencing platform to detect more than 3,100 high quality single nucleotide polymorphisms in each population. A total of 130 quantitative trait loci (QTL) were detected on 20 chromosomes, six of which were associated with NUE and N-related traits in multiple testing environments. Two of the six QTL for NUE were associated with known photoperiod (Ppd-D1 on chromosome 2D) and disease resistance (FHB-4A) genes, two were reported in previous investigations, and one QTL, QNue.151-1D, was novel. The NUE QTL on 1D, 6A, 7A, and 7D had LOD scores ranging from 2.63 to 8.33 and explained up to 18.1% of the phenotypic variation. The QTL identified in this study have potential for marker-assisted breeding for NUE traits in soft red winter wheat.

Flag leaf size and posture of bread wheat: genetic dissection, QTL validation and their relationships with yield-related traits

Major and environmentally stable QTL for flag leaf-related traits in wheat were identified and validated across ten environments using six populations with different genetic backgrounds. Flag leaf size and posture are two important factors of "ideotype" in wheat. Despite numerous studies on genetic analysis of flag leaf size including flag leaf length (FLL), width (FLW), area (FLA) and the ratio of length/width (FLR), few have focused on flag leaf posture including flag leaf angle (FLANG), opening angle (FLOA) and bend angle (FLBA). Further, the numbers of major, environmentally stable and verified genetic loci for flag leaf-related traits are limited. In this study, QTL for FLL, FLW, FLA, FLR, FLANG, FLOA and FLBA were identified based on a recombinant inbred line population together with values from up to ten different environments. Totally, eight major and stably expressed QTL were identified. Three co-located chromosomal intervals for seven major QTL were identified. The five major QTL QFll.sicau-5B.3 and QFll.sicau-2D.3 for FLL, QFlr.sicau-5B for FLR, QFlw.sicau-2D for FLW and QFla.sicau-2D for FLA were successfully validated by the tightly linked Kompetitive Allele Specific PCR (KASP) markers in the other five populations with different genetic backgrounds. A few genes related to leaf growth and development in intervals for these major QTL were predicated. Significant relationships between flag leaf- and yield-related traits were evidenced by analyses of Pearson correlations, conditional QTL and genetic mapping. Taken together, these results provide valuable information for understanding flag leaf size and posture of "ideotype" as well as fine mapping and breeding utilization of promising loci in bread wheat.

Construction of a high-density genetic map and QTL mapping of leaf traits and plant growth in an interspecific F1 population of Catalpa bungei × Catalpa duclouxii Dode

BACKGROUND

Catalpa bungei is an important tree species used for timber in China and widely cultivated for economic and ornamental purposes. A high-density linkage map of C. bungei would be an efficient tool not only for identifying key quantitative trait loci (QTLs) that affect important traits, such as plant growth and leaf traits, but also for other genetic studies.

RESULTS

Restriction site-associated DNA sequencing (RAD-seq) was used to identify molecular markers and construct a genetic map. Approximately 280.77 Gb of clean data were obtained after sequencing, and in total, 25,614,295 single nucleotide polymorphisms (SNPs) and 2,871,647 insertions-deletions (InDels) were initially identified in the genomes of 200 individuals of a C. bungei (7080) × Catalpa duclouxii (16-PJ-3) F₁ population and their parents. Finally, 9072 SNP and 521 InDel markers that satisfied the requirements for constructing a genetic map were obtained. The integrated genetic map contained 9593 pleomorphic markers in 20 linkage groups and spanned 3151.63 cM, with an average distance between adjacent markers of 0.32 cM. Twenty QTLs for seven leaf traits and 13 QTLs for plant height at five successive time points were identified using our genetic map by inclusive composite interval mapping (ICIM). Q16-60 was identified as a QTL for five leaf traits, and three significant QTLs (Q9-1, Q18-66 and Q18-73) associated with plant growth were detected at least twice. Genome annotation suggested that a cyclin gene participates in leaf trait development, while the growth of C. bungei may be influenced by CDC48C and genes associated with phytohormone synthesis.

CONCLUSIONS

This is the first genetic map constructed in C. bungei and will be a useful tool for further genetic study, molecular marker-assisted breeding and genome assembly.

Linkage mapping and quantitative trait loci analysis of sweetness and other fruit quality traits in papaya

BACKGROUND

The identification and characterisation of quantitative trait loci (QTL) is an important step towards identifying functional sequences underpinning important crop traits and for developing accurate markers for selective breeding strategies. In this study, a genotyping-by-sequencing (GBS) approach detected QTL conditioning desirable fruit quality traits in papaya.

RESULTS

For this, a linkage map was constructed comprising 219 single nucleotide polymorphism (SNP) loci across 10 linkage groups and covering 509 centiMorgan (cM). In total, 21 QTLs were identified for seven key fruit quality traits, including flesh sweetness, fruit weight, fruit length, fruit width skin freckle, flesh thickness and fruit firmness. Several QTL for flesh sweetness, fruit weight, length, width and firmness were stable across harvest years and individually explained up to 19.8% of the phenotypic variance of a particular trait. Where possible, candidate genes were proposed and explored further for their application to marker-assisted breeding.

CONCLUSIONS

This study has extended knowledge on the inheritance and genetic control for key papaya physiological and fruit quality traits. Candidate genes together with associated SNP markers represent a valuable resource for the future of strategic selective breeding of elite Australian papaya cultivars.

Identification of quantitative trait loci for kernel traits in a wheat cultivar Chuannong16

Background

Kernel length (KL), kernel width (KW) and thousand-kernel weight (TKW) are key agronomic traits in wheat breeding. Chuannong16 (‘CN16’) is a commercial cultivar with significantly longer kernels than the line ‘20828’. To identify and characterize potential alleles from CN16 controlling KL, the previously developed recombinant inbred line (RIL) population derived from the cross ‘20828’ × ‘CN16’ and the genetic map constructed by the Wheat55K SNP array and SSR markers were used to perform quantitative trait locus/loci (QTL) analyses for kernel traits.

Results

A total of 11 putative QTL associated with kernel traits were identified and they were located on chromosomes 1A (2 QTL), 2B (2 QTL), 2D (3 QTL), 3D, 4A, 6A, and 7A, respectively. Among them, three major QTL, QKL.sicau-2D, QKW.sicau-2D and QTKW.sicau-2D, controlling KL, KW and TKW, respectively, were detected in three different environments. Respectively, they explained 10.88–18.85%, 17.21–21.49% and 10.01–23.20% of the phenotypic variance. Further, they were genetically mapped in the same interval on chromosome 2DS. A previously developed kompetitive allele-specific PCR (KASP) marker KASP-AX-94721936 was integrated in the genetic map and QTL re-mapping finally located the three major QTL in a 1- cM region flanked by AX-111096297 and KASP-AX-94721936. Another two co-located QTL intervals for KL and TKW were also identified. A few predicted genes involved in regulation of kernel growth and development were identified in the intervals of these identified QTL. Significant relationships between kernel traits and spikelet number per spike and anthesis date were detected and discussed.

Conclusions

Three major and stably expressed QTL associated with KL, KW, and TKW were identified. A KASP marker tightly linked to these three major QTL was integrated. These findings provide information for subsequent fine mapping and cloning the three co-localized major QTL for kernel traits.

Genotyping-by-sequencing based QTL mapping for rice grain yield under reproductive stage drought stress tolerance

QTLs for rice grain yield under reproductive stage drought stress (qDTY) identified earlier with low density markers have shown linkage drag and need to be fine mapped before their utilization in breeding programs. In this study, genotyping-by-sequencing (GBS) based high-density linkage map of rice was developed using two BC₁F₃ mapping populations namely Swarna*2/Dular (3929 SNPs covering 1454.68 cM) and IR11N121*2/Aus196 (1191 SNPs covering 1399.68 cM) with average marker density of 0.37 cM to 1.18 cM respectively. In total, six qDTY QTLs including three consistent effect QTLs were identified in Swarna*2/Dular while eight qDTY QTLs including two consistent effect QTLs were identified in IR11N121*2/Aus 196 mapping population. Comparative analysis revealed four stable and novel QTLs (qDTY_2.4, qDTY_3.3, qDTY_6.3, and qDTY_11.2) which explained 8.62 to 14.92% PVE. However, one of the identified stable grain yield QTL qDTY_1.1 in both the populations was located nearly at the same physical position of an earlier mapped major qDTY QTL. Further, the effect of the identified qDTY_1.1 was validated in a subset of lines derived from five mapping populations confirming robustness of qDTY_1.1 across various genetic backgrounds/seasons. The study successfully identified stable grain yield QTLs free from undesirable linkages of tall plant height/early maturity utilizing high density linkage maps.

Genetic diversity, linkage disequilibrium, and population structure analysis of the tea plant (Camellia sinensis) from an origin center, Guizhou plateau, using genome-wide SNPs developed by genotyping-by-sequencing

BACKGROUND

To efficiently protect and exploit germplasm resources for marker development and breeding purposes, we must accurately depict the features of the tea populations. This study focuses on the Camellia sinensis (C. sinensis) population and aims to (i) identify single nucleotide polymorphisms (SNPs) on the genome level, (ii) investigate the genetic diversity and population structure, and (iii) characterize the linkage disequilibrium (LD) pattern to facilitate next genome-wide association mapping and marker-assisted selection.

RESULTS

We collected 415 tea accessions from the Origin Center and analyzed the genetic diversity, population structure and LD pattern using the genotyping-by-sequencing (GBS) approach. A total of 79,016 high-quality SNPs were identified; the polymorphism information content (PIC) and genetic diversity (GD) based on these SNPs showed a higher level of genetic diversity in cultivated type than in wild type. The 415 accessions were clustered into three groups by STRUCTURE software and confirmed using principal component analyses (PCA)-wild type, cultivated type, and admixed wild type. However, unweighted pair group method with arithmetic mean (UPGMA) trees indicated the accessions should be grouped into more clusters. Further analyses identified four groups, the Pure Wild Type, Admixed Wild Type, ancient landraces and modern landraces using STRUCTURE, and the results were confirmed by PCA and UPGMA tree method. A higher level of genetic diversity was detected in ancient landraces and Admixed Wild Type than that in the Pure Wild Type and modern landraces. The highest differentiation was between the Pure Wild Type and modern landraces. A relatively fast LD decay with a short range (kb) was observed, and the LD decays of four inferred populations were different.

CONCLUSIONS

This study is, to our knowledge, the first population genetic analysis of tea germplasm from the Origin Center, Guizhou Plateau, using GBS. The LD pattern, population structure and genetic differentiation of the tea population revealed by our study will benefit further genetic studies, germplasm protection, and breeding.

Drought Stress Tolerance in Wheat and Barley: Advances in Physiology, Breeding and Genetics Research

Climate change is a major threat to most of the agricultural crops grown in tropical and sub-tropical areas globally. Drought stress is one of the consequences of climate change that has a negative impact on crop growth and yield. In the past, many simulation models were proposed to predict climate change and drought occurrences, and it is extremely important to improve essential crops to meet the challenges of drought stress which limits crop productivity and production. Wheat and barley are among the most common and widely used crops due to their economic and social values. Many parts of the world depend on these two crops for food and feed, and both crops are vulnerable to drought stress. Improving drought stress tolerance is a very challenging task for wheat and barley researchers and more research is needed to better understand this stress. The progress made in understanding drought tolerance is due to advances in three main research areas: physiology, breeding, and genetic research. The physiology research focused on the physiological and biochemical metabolic pathways that plants use when exposed to drought stress. New wheat and barley genotypes having a high degree of drought tolerance are produced through breeding by making crosses from promising drought-tolerant genotypes and selecting among their progeny. Also, identifying genes contributing to drought tolerance is very important. Previous studies showed that drought tolerance is a polygenic trait and genetic constitution will help to dissect the gene network(s) controlling drought tolerance. This review explores the recent advances in these three research areas to improve drought tolerance in wheat and barley.

Drought Stress Tolerance in Wheat and Barley: Advances in Physiology, Breeding and Genetics Research

Climate change is a major threat to most of the agricultural crops grown in tropical and sub-tropical areas globally. Drought stress is one of the consequences of climate change that has a negative impact on crop growth and yield. In the past, many simulation models were proposed to predict climate change and drought occurrences, and it is extremely important to improve essential crops to meet the challenges of drought stress which limits crop productivity and production. Wheat and barley are among the most common and widely used crops due to their economic and social values. Many parts of the world depend on these two crops for food and feed, and both crops are vulnerable to drought stress. Improving drought stress tolerance is a very challenging task for wheat and barley researchers and more research is needed to better understand this stress. The progress made in understanding drought tolerance is due to advances in three main research areas: physiology, breeding, and genetic research. The physiology research focused on the physiological and biochemical metabolic pathways that plants use when exposed to drought stress. New wheat and barley genotypes having a high degree of drought tolerance are produced through breeding by making crosses from promising drought-tolerant genotypes and selecting among their progeny. Also, identifying genes contributing to drought tolerance is very important. Previous studies showed that drought tolerance is a polygenic trait and genetic constitution will help to dissect the gene network(s) controlling drought tolerance. This review explores the recent advances in these three research areas to improve drought tolerance in wheat and barley.

Identification of quantitative trait loci associated with flowering time in perilla using genotyping-by-sequencing

Understanding the transition to the reproductive period is important for crop breeding. This information can facilitate the production of novel varieties that are better adapted to local environments or changing climatic conditions. Here, we report the development of a high-density linkage map based on genotyping-by-sequencing (GBS) for the genus perilla. Through GBS library construction and Illumina sequencing of an F₂ population, a total of 9607 single-nucleotide polymorphism (SNP) markers were developed. The ten-group linkage map of 1309.39 cM contained 2518 markers, with an average marker density of 0.56 cM per linkage group (LG). Using this map, a total of six QTLs were identified. These quantitative trait loci (QTLs) are associated with three traits related to flowering time: days to visible flower bud, days to flowering, and days to maturity. Ortholog analysis conducted with known genes involved in the regulation of flowering time among different crop species identified GI, CO and ELF4 as putative perilla orthologs that are closely linked to the QTL regions associated with flowering time. These results provide a foundation that will be useful for future studies of flowering time in perilla using fine mapping, and marker-assisted selection for the development of new varieties of perilla.

Linkage-based genome assembly improvement of oil palm (Elaeis guineensis)

Meiotic crossovers in outbred species, such as oil palm (Elaeis guineensis Jacq., 2n = 32) contribute to allelic re-assortment in the genome. Such genetic variation is usually exploited in breeding to combine positive alleles for trait superiority. A good quality reference genome is essential for identifying the genetic factors underlying traits of interest through linkage or association studies. At the moment, an AVROS pisifera genome is publicly available for oil palm. Distribution and frequency of crossovers throughout chromosomes in different origins of oil palm are still unclear. Hence, an ultrahigh-density genomic linkage map of a commercial Deli dura x AVROS pisifera family was constructed using the OP200K SNP array, to evaluate the genetic alignment with the genome assembly. A total of 27,890 linked SNP markers generated a total map length of 1,151.7 cM and an average mapping interval of 0.04 cM. Nineteen linkage groups represented 16 pseudo-chromosomes of oil palm, with 61.7% of the mapped SNPs present in the published genome. Meanwhile, the physical map was also successfully extended from 658 Mb to 969 Mb by assigning unplaced scaffolds to the pseudo-chromosomes. A genic linkage map with major representation of sugar and lipid biosynthesis pathways was subsequently built for future studies on oil related quantitative trait loci (QTL). This study improves the current physical genome of the commercial oil palm, and provides important insights into its recombination landscape, eventually unlocking the full potential genome sequence-enabled biology for oil palm.

Construction of a high-density linkage map and QTL mapping for important agronomic traits in Stylosanthes guianensis (Aubl.) Sw

Stylosanthes guianensis (Aubl.) Sw. is an economically important pasture and forage legume in tropical regions of the world. Genetic improvement of the crop can be enhanced through marker-assisted breeding. However, neither single nucleotide polymorphism (SNP) markers nor SNP-based genetic linkage map has been previously reported. In this study, a high-quality genetic linkage map of 2572 SNP markers for S. guianensis is generated using amplified-fragment single nucleotide polymorphism and methylation (AFSM) approach. The genetic map has 10 linkage groups (LGs), which spanned 2226.6 cM, with an average genetic distance of 0.87 cM between adjacent markers. Genetic mapping of quantitative trait loci (QTLs) for important agronomic traits such as yield-related and nutritional or quality-related traits was performed using F₂ progeny of a cross between a male-sterile female parent TPRC1979 and male parent TPRCR273 with contrasting phenotypes for morphological and physiological traits. A total of 30 QTLs for 8 yield-related traits and 18 QTLs for 4 nutritional or quality-related traits are mapped on the linkage map. Both the high-quality genetic linkage map and the QTL mapping for important agronomic traits described here will provide valuable genetic resources for marker-assisted selection for S. guianensis.

Rapid gene cloning in cereals

The large and complex genomes of many cereals hindered cloning efforts in the past. Advances in genomics now allow the rapid cloning of genes from humanity's most valuable crops. The past two decades were characterized by a genomics revolution that entailed profound changes to crop research, plant breeding, and agriculture. Today, high-quality reference sequences are available for all major cereal crop species. Large resequencing and pan-genome projects start to reveal a more comprehensive picture of the genetic makeup and the diversity among domesticated cereals and their wild relatives. These technological advancements will have a dramatic effect on dissecting genotype-phenotype associations and on gene cloning. In this review, we will highlight the status of the genomic resources available for various cereal crops and we will discuss their implications for gene cloning. A particular focus will be given to the cereal species barley and wheat, which are characterized by very large and complex genomes that have been inaccessible to rapid gene cloning until recently. With the advancements in genomics and the development of several rapid gene-cloning methods, it has now become feasible to tackle the cloning of most agriculturally important genes, even in wheat and barley.

Dense genotyping-by-sequencing linkage maps of two Synthetic W7984×Opata reference populations provide insights into wheat structural diversity

Wheat (Triticum aestivum) genetic maps are a key enabling tool for genetic studies. We used genotyping-by-sequencing-(GBS) derived markers to map recombinant inbred line (RIL) and doubled haploid (DH) populations from crosses of W7984 by Opata, and used the maps to explore features of recombination control. The RIL and DH populations, SynOpRIL and SynOpDH, were composed of 906 and 92 individuals, respectively. Two high-density genetic linkage framework maps were constructed of 2,842 and 2,961 cM, harboring 3,634 and 6,580 markers, respectively. Using imputation, we added 43,013 and 86,042 markers to the SynOpRIL and SynOpDH maps. We observed preferential recombination in telomeric regions and reduced recombination in pericentromeric regions. Recombination rates varied between subgenomes, with the D genomes of the two populations exhibiting the highest recombination rates of 0.26-0.27 cM/Mb. QTL mapping identified two additive and three epistatic loci associated with crossover number. Additionally, we used published POPSEQ data from SynOpDH to explore the structural variation in W7984 and Opata. We found that chromosome 5AS is missing from W7984. We also found 2,332 variations larger than 100 kb. Structural variants were more abundant in distal regions, and overlapped 9,196 genes. The two maps provide a resource for trait mapping and genomic-assisted breeding.

Imputation accuracy of wheat genotyping-by-sequencing (GBS) data using barley and wheat genome references

Genotyping-by-sequencing (GBS) provides high SNP coverage and has recently emerged as a popular technology for genetic and breeding applications in bread wheat (Triticum aestivum L.) and many other plant species. Although GBS can discover millions of SNPs, a high rate of missing data is a major concern for many applications. Accurate imputation of those missing data can significantly improve the utility of GBS data. This study compared imputation accuracies among four genome references including three wheat references (Chinese Spring survey sequence, W7984, and IWGSC RefSeq v1.0) and one barley reference genome by comparing imputed data derived from low-depth sequencing to actual data from high-depth sequencing. After imputation, the average number of imputed data points was the highest in the B genome (~48.99%). The D genome had the lowest imputed data points (~15.02%) but the highest imputation accuracy. Among the four reference genomes, IWGSC RefSeq v1.0 reference provided the most imputed data points, but the lowest imputation accuracy for the SNPs with < 10% minor allele frequency (MAF). The W7984 reference, however, provided the highest imputation accuracy for the SNPs with < 10% MAF.

Genome-Wide Association Study Reveals Novel Genomic Regions for Grain Yield and Yield-Related Traits in Drought-Stressed Synthetic Hexaploid Wheat

Synthetic hexaploid wheat (SHW; 2n = 6x = 42, AABBDD, Triticum aestivum L.) is produced from an interspecific cross between durum wheat (2n = 4x = 28, AABB, T. turgidum L.) and goat grass (2n = 2x = 14, DD, Aegilops tauschii Coss.) and is reported to have significant novel alleles-controlling biotic and abiotic stresses resistance. A genome-wide association study (GWAS) was conducted to unravel these loci [marker⁻trait associations (MTAs)] using 35,648 genotyping-by-sequencing-derived single nucleotide polymorphisms in 123 SHWs. We identified 90 novel MTAs (45, 11, and 34 on the A, B, and D genomes, respectively) and haplotype blocks associated with grain yield and yield-related traits including root traits under drought stress. The phenotypic variance explained by the MTAs ranged from 1.1% to 32.3%. Most of the MTAs (120 out of 194) identified were found in genes, and of these 45 MTAs were in genes annotated as having a potential role in drought stress. This result provides further evidence for the reliability of MTAs identified. The large number of MTAs (53) identified especially on the D-genome demonstrate the potential of SHWs for elucidating the genetic architecture of complex traits and provide an opportunity for further improvement of wheat under rapidly changing climatic conditions.

Characterizing Virulence of the Pyrenophora tritici-repentis Isolates Lacking Both ToxA and ToxB Genes

The fungus Pyrenophora tritici-repentis (Ptr) causes tan spot of wheat crops, which is an important disease worldwide. Based on the production of the three known necrotrophic effectors (NEs), the fungal isolates are classified into eight races with race 4 producing no known NEs. From a laboratory cross between 86⁻124 (race 2 carrying the ToxA gene for the production of Ptr ToxA) and DW5 (race 5 carrying the ToxB gene for the production of Ptr ToxB), we have obtained some Ptr isolates lacking both the ToxA and ToxB genes, which, by definition, should be classified as race 4. In this work, we characterized virulence of two of these isolates called B16 and B17 by inoculating them onto various common wheat (Triticum aestivum L.) and durum (T. turgidum L.) genotypes. It was found that the two isolates still caused disease on some genotypes of both common and durum wheat. Disease evaluations were also conducted in recombinant inbred line populations derived from two hard red winter wheat cultivars: Harry and Wesley. QTL mapping in this population revealed that three genomic regions were significantly associated with disease, which are different from the three known NE sensitivity loci. This result further indicates the existence of other NE-host sensitivity gene interactions in the wheat tan spot disease system.

Genetic linkage map and QTL identification for adventitious rooting traits in red gum eucalypts

The eucalypt species, Eucalyptus tereticornis and Eucalyptus camaldulensis, show tolerance to drought and salinity conditions, respectively, and are widely cultivated in arid and semiarid regions of tropical countries. In this study, genetic linkage map was developed for interspecific cross E. tereticornis × E. camaldulensis using pseudo-testcross strategy with simple sequence repeats (SSRs), intersimple sequence repeats (ISSRs), and sequence-related amplified polymorphism (SRAP) markers. The consensus genetic map comprised totally 283 markers with 84 SSRs, 94 ISSRs, and 105 SRAP markers on 11 linkage groups spanning 1163.4 cM genetic distance. Blasting the SSR sequences against E. grandis sequences allowed an alignment of 64% and the average ratio of genetic-to-physical distance was 1.7 Mbp/cM, which strengths the evidence that high amount of synteny and colinearity exists among eucalypts genome. Blast searches also revealed that 37% of SSRs had homologies with genes, which could potentially be used in the variety of downstream applications including candidate gene polymorphism. Quantitative trait loci (QTL) analysis for adventitious rooting traits revealed six QTL for rooting percent and root length on five chromosomes with interval and composite interval mapping. All the QTL explained 12.0-14.7% of the phenotypic variance, showing the involvement of major effect QTL on adventitious rooting traits. Increasing the density of markers would facilitate the detection of more number of small-effect QTL and also underpinning the genes involved in rooting process.

Genetic Diversity and Population Structure of F3:6 Nebraska Winter Wheat Genotypes Using Genotyping-By-Sequencing

The availability of information on the genetic diversity and population structure in wheat (Triticum aestivum L.) breeding lines will help wheat breeders to better use their genetic resources and manage genetic variation in their breeding program. The recent advances in sequencing technology provide the opportunity to identify tens or hundreds of thousands of single nucleotide polymorphism (SNPs) in large genome species (e.g., wheat). These SNPs can be utilized for understanding genetic diversity and performing genome wide association studies (GWAS) for complex traits. In this study, the genetic diversity and population structure were investigated in a set of 230 genotypes (F_3:6) derived from various crosses as a prerequisite for GWAS and genomic selection. Genotyping-by-sequencing provided 25,566 high-quality SNPs. The polymorphism information content (PIC) across chromosomes ranged from 0.09 to 0.37 with an average of 0.23. The distribution of SNPs markers on the 21 chromosomes ranged from 319 on chromosome 3D to 2,370 on chromosome 3B. The analysis of population structure revealed three subpopulations (G1, G2, and G3). Analysis of molecular variance identified 8% variance among and 92% within subpopulations. Of the three subpopulations, G2 had the highest level of genetic diversity based on three genetic diversity indices: Shannon’s information index (I) = 0.494, diversity index (h) = 0.328 and unbiased diversity index (uh) = 0.331, while G3 had lowest level of genetic diversity (I = 0.348, h = 0.226 and uh = 0.236). This high genetic diversity identified among the subpopulations can be used to develop new wheat cultivars.