High-density Genetic Linkage Research Articles

Construction of a high density genetic linkage map to define the locus conferring seedlessness from Mukaku Kishu mandarin.

Mukaku Kishu ('MK'), a small sized mandarin, is an important source of seedlessness in citrus breeding. Identification and mapping the gene(s) governing 'MK' seedlessness will expedite seedless cultivar development. In this study, two 'MK'-derived mapping populations- LB8-9 Sugar Belle® ('SB') × 'MK' (N=97) and Daisy ('D') × 'MK' (N=68) were genotyped using an Axiom_Citrus56 Array encompassing 58,433 SNP probe sets, and population specific male and female parent linkage maps were constructed. The parental maps of each population were integrated to produce sub-composite maps, which were further merged to develop a consensus linkage map. All the parental maps (except 'MK_D') had nine major linkage groups, and contained 930 ('SB'), 810 ('MK_SB'), 776 ('D') and 707 ('MK_D') SNPs. The linkage maps displayed 96.9 ('MK_D') to 98.5% ('SB') chromosomal synteny with the reference Clementine genome. The consensus map was comprised of 2588 markers including a phenotypic seedless (Fs)-locus and spanned a genetic distance of 1406.84 cM, with an average marker distance of 0.54 cM, which is substantially lower than the reference Clementine map. For the phenotypic Fs-locus, the distribution of seedy and seedless progenies in both 'SB' × 'MK' (55:42, χ2 = 1.74) and 'D' × 'MK' populations (33:35, χ2 = 0.06) followed a test cross pattern. The Fs-locus mapped on chromosome 5 with SNP marker 'AX-160417325' at 7.4 cM in 'MK_SB' map and between two SNP markers 'AX-160536283' and 'AX-160906995' at a distance of 2.4 and 4.9 cM, respectively in 'MK_D' map. The SNPs 'AX-160417325' and 'AX-160536283' correctly predicted seedlessness of 25-91.9% progenies in this study. Based on the alignment of flanking SNP markers to the Clementine reference genome, the candidate gene for seedlessness hovered in a ~ 6.0 Mb region between 3.97 Mb (AX-160906995) to 10.00 Mb (AX-160536283). This region has 131 genes of which 13 genes (belonging to seven gene families) reportedly express in seed coat or developing embryo. The findings of the study will prove helpful in directing future research for fine mapping this region and eventually underpinning the exact causative gene governing seedlessness in 'MK'.

Identification of QTLs and candidate genes controlling berry size in table grape by integrating QTL and transcriptomic analysis

• QTLs for berry weight were stably identified on Chrs5, 11, and 17, respectively. • QTLs for berry length were stably identified on Chrs5, 8, 15, and 17, respectively. • 6 potential candidate genes underlying the stable QTLs were highlighted. • VIT_05s0020g03980, VIT_08s0032g01110 and VIT_15s0021g02460 belonging to the IQD, YABBY, and CNR families could have a significant effect on the berry size variation in grapevine. Grape berry size is one of important external quality attributes affecting consumers’ preference, but also a component of yield, and thus one of the major concerns of grapevine breeders. However, as a complex quantitative trait under polygenic control, its genetic mechanism is still not fully understood. In the present work, berry weight, berry length and berry diameter of the grapes of 160 F1 progenies from an interspecific cross between ‘Moldova’ ( V. labruscana × V. vinifera ) and ‘Ruiduxiangyu’ ( V. vinifera ) were evaluated at the mature stage over four consecutive years. The significant QTLs and the underlying candidate genes for berry size related traits were identified by integrating with QTL mapping, RNA-seq, phylogenetic, and allelic variants analyses. 15 QTLs mainly on the Chr5, 11, and 17 linked to the trait of berry weight, 17 QTLs contributed to the trait of berry length, and 8 QTLs associated with berry diameter were detected based on high density genetic linkage maps over four years respectively. 6 prominent candidate genes including VIT_05s0020g03980 (protein IQ-DOMAIN 14-like), VIT_08s0032g01110 (putative axial regulator YABBY 2-like), VIT_15s0021g02460 (putative cell number regulator 6), VIT_17s0053g00700 (unnamed protein), VIT_17s0053g00990 (predicted expansin-A15) and VIT_11s0052g00840 (PREDICTED AP2-like ethylene-responsive transcription factor AIL5-like) were further highlighted underlying the QTLs. The results obtained in this study provide new insights into berry size variation in grapevine.

Construction of High-Density Genetic Map and Identification of a Bruchid Resistance Locus in Mung Bean (Vigna radiata L.).

Mung bean (Vigna radiata L.) is an economically important grain legume cultivated in Asian countries. High-density genetic linkage is a valuable and effective tool for mapping quantitative trait loci (QTL). In the current study, a high-resolution genetic map containing 4,180 single-nucleotide polymorphisms (SNPs) was assigned to 11 linkage groups (LGs) and spanning 1,751.39 cM in length was constructed for mung bean, and the average distance between adjacent markers was 0.42 cM. Bruchids (Callosobruchus spp.) cause significant damage to and loss of legume seeds. A locus for bruchid resistance was detected. The gene Vradi05g03810, encoding a probable resistance-specific protein, was found to be the most likely key candidate gene in mung beans. A 69-bp sequence deletion was identified in the coding region by comparing the cDNA sequences of bruchid-resistant and bruchid-susceptible lines. This SNP-based high-density linkage map is one of the first to be constructed across the mung bean genome. This map will not only facilitate the genetic mapping of genes or complex loci that control important agronomic traits but also offer a tool for promoting future genetics and comparative genomic studies in Vigna.

Construction of a high-density genetic map and mapping of growth related QTLs in the grass carp (Ctenopharyngodon idellus)

BackgroundGrass carp (Ctenopharyngodon idellus) are important species in Asian aquaculture. A draft genome for grass carp has already been published in 2015. However, there is still a requirement for a suitable genetic linkage map to arrange scaffolds on chromosomal frameworks. QTL analysis is a powerful tool to detect key locations for quantitative traits, especially in aquaculture. There no growth related QTLs of grass carp have been published yet. Even the growth trait is one of the focuses in grass carp culture.ResultsIn this study, a pair of distantly related parent grass carps and their 100 six-month-old full-sib offspring were used to construct a high-density genetic map with 6429 single nucleotide polymorphisms (SNPs) by 2b-RAD technology. The total length of the consensus map is 5553.43 cM with the average marker interval of 1.92 cM. The map has a good collinearity with both the grass carp draft genome and the zebrafish genome, and it assembled 89.91% of the draft genome to a chromosomal level. Additionally, according to the growth-related traits of progenies, 30 quantitative trait loci (QTLs), including 7 for body weight, 9 for body length, 5 for body height and 9 for total length, were identified in 16 locations on 5 linkage groups. The phenotypic variance explained for these QTLs varies from 13.4 to 21.6%. Finally, 17 genes located in these regions were considered to be growth-related because they either had functional mutations predicted from the resequencing data of the parents.ConclusionA high density genetic linkage map of grass carp was built and it assembled the draft genome to a chromosomal level. Thirty growth related QTLs were detected. After the cross analysis of Parents resequencing data, 17 candidate genes were obtained for further researches.

QTL mapping of seed germination-related traits in <italic>Brassica napus</italic> L. under aluminum toxicity stress

<p indent=0mm>With the aggravation of soil acidification, aluminum toxicity has become one of the important stress factors that affect crop seed germination quality and crop yield. There have been many reports on QTL mapping and candidate gene screening for aluminum tolerance related traits in crops, but few reports on QTL mapping for aluminum tolerance during germination in <italic>Brassica napus</italic> L. The seed germination test was conducted on the recombinant inbred line population treated with <sc>80 µg mL^-1</sc> aluminum solution and with distilled water as control. Germination potential was investigated at <sc>3 d,</sc> germination rate was investigated at <sc>7 d,</sc> root length, bud length and dry weight were measured, and the relative values of various characters were calculated. Based on 6K SNP chip and combined with high density genetic linkage map, we detected 23 QTLs for five traits in rape germination period. QTLs for relative germination potential, relative germination rate, relative root length, relative bud length and relative dry weight were 9, 1, 4, 5, and 4 respectively, covering A and C genomes, with LOD values from 3.00 to 5.26, and interpretable phenotypic variation from 7.70% to 13.10%. According to the confidence interval sequence of each QTL, 30 candidate genes related to aluminum stress were screened. <italic>ALMT1</italic> gene and <italic>MATE</italic> gene are related to the synthesis and secretion of organic acids, which mainly enhance the aluminum tolerance of plants through the secretion of organic acids such as malic acid, citric acid and oxalic acid. <italic>STOP1</italic> gene, <italic>NAC </italic>gene and <italic>RAP2.4 </italic>gene all belong to transcription activation factors, which enhance the resistance of plants by inducing the expression of aluminum tolerance genes. ABC transporter, membrane protein transporter, GDSL lipase enhance aluminum tolerance of plants by reducing accumulation of toxic substances on plasma membrane or discharging toxic substances out of body. Peroxidase and cytochrome P450 are genes related to oxidative stress, which have the functions of preventing oxidative damage of plant cells and resisting stress. At the same time, many genes encoding stress proteins were found, which play an important role in various stress reactions. The results of this study provide a theoretical basis for the cultivation of aluminum-tolerant rape varieties and the functional research of subsequent genes.

Identification of Quantitative Trait Loci Controlling Ethylene Production in Germinating Seeds in Maize (Zea mays L.)

Plant seed germination is a crucial developmental event that has significant effects on seedling establishment and yield production. This process is controlled by multiple intrinsic signals, particularly phytohormones. The gaseous hormone ethylene stimulates seed germination; however, the genetic basis of ethylene production in maize during seed germination remains poorly understood. In this study, we quantified the diversity of germination among 14 inbred lines representing the parental materials corresponding to multiple recombinant inbred line (RIL) mapping populations. Quantitative trait loci (QTLs) controlling ethylene production were then identified in germinating seeds from an RIL population constructed from two parental lines showing differences in both germination speed and ethylene production during germination. To explore the possible genetic correlations of ethylene production with other traits, seed germination and seed weight were evaluated using the same batch of samples. On the basis of high-density single nucleotide polymorphism-based genetic linkage maps, we detected three QTLs for ethylene production in germinating seeds, three QTLs for seed germination, and four QTLs for seed weight, with each QTL explaining 5.8%–13.2% of the phenotypic variation of the trait. No QTLs were observed to be co-localized, suggesting that the genetic bases underlying the three traits are largely different. Our findings reveal three chromosomal regions responsible for ethylene production during seed germination, and provide a valuable reference for the future investigation of the genetic mechanism underlying the role of the stress hormone ethylene in maize germination control under unfavourable external conditions.

A high density genetic map by whole-genome resequencing for QTL fine-mapping and dissecting candidate genes for growth or sex traits in the pearl oyster (Pinctada fucata martensii)

Pinctada fucata martensii is an economically important shellfish in pearl production. Marker-assisted breeding can be accelerated by whole-genome resequencing (WGR), which is faster and more precise for detecting recombination breakpoints and constructing genetic maps than marker-based genotyping methods. To obtain more genetic information and dissect the loci associated with growth- or sex-related traits, we have constructed a high density genetic linkage map consisting of 4469 recombination bin markers (91,448 SNPs) covering 2232.14 cM, with an average distance of 0.50 cM based on WGR. Thirty-two quantitative trait loci (QTL) related to seven growth traits and one sex trait were mapped in 10 linkage groups (LGs) with 695 candidate genes annotated, and QTLs related to growth traits were mainly mapped on LG4. The combination analysis of QTL mapping and bulked segregant analysis (BSA) revealed that many receptor genes, such as PfNPYR, PfTRHR, PfGABARB, PfSSTR-2, and PfDD2R, were involved in neuroendocrine regulation, which is important in growth and reproduction. Moreover, transcriptome analysis of pearl oyster exhibiting extreme opposite traits for shell length revealed that four differentially expressed genes (DEGs) were located on the regions of QTLs related to growth traits, and three genes were consistent with the transcriptome after validation by real-time quantitative PCR (RT-qPCR). This study provided new insight into the molecular mechanism of candidate genes determining traits and provided an ideal platform for MAS by dissecting QTL and candidate genes related to economical traits in P. f. martensii.

Legume genomics and transcriptomics: From classic breeding to modern technologies.

Legumes are essential and play a significant role in maintaining food standards and augmenting physiochemical soil properties through the biological nitrogen fixation process. Biotic and abiotic factors are the main factors limiting legume production. Classical breeding methodologies have been explored extensively about the problem of truncated yield in legumes but have not succeeded at the desired rate. Conventional breeding improved legume genotypes but with more resources and time. Recently, the invention of next-generation sequencing (NGS) and high-throughput methods for genotyping have opened new avenues for research and developments in legume studies. During the last decade, genome sequencing for many legume crops documented. Sequencing and re-sequencing of important legume species have made structural variation and functional genomics conceivable. NGS and other molecular techniques such as the development of markers; genotyping; high density genetic linkage maps; quantitative trait loci (QTLs) identification, expressed sequence tags (ESTs), single nucleotide polymorphisms (SNPs); and transcription factors incorporated into existing breeding technologies have made possible the accurate and accelerated delivery of information for researchers. The application of genome sequencing, RNA sequencing (transcriptome sequencing), and DNA sequencing (re-sequencing) provide considerable insights for legume development and improvement programs.Moreover, RNA-Seq helps to characterize genes, including differentially expressed genes, and can be applied for functional genomics studies, especially when there is limited information available for the studied genomes. Genome-based crop development studies and the availability of genomics data as well as decision-making gears look be specific for breeding programs. This review mainly presents an overview of the path from classical breeding to new emerging genomics tools, which will trigger and accelerate genomics-assisted breeding for recognition of novel genes for yield and quality characters for sustainable legume crop production.

GeneHummus: an R package to define gene families and their expression in legumes and beyond

BackgroundDuring the last decade, plant biotechnological laboratories have sparked a monumental revolution with the rapid development of next sequencing technologies at affordable prices. Soon, these sequencing technologies and assembling of whole genomes will extend beyond the plant computational biologists and become commonplace within the plant biology disciplines. The current availability of large-scale genomic resources for non-traditional plant model systems (the so-called ‘orphan crops’) is enabling the construction of high-density integrated physical and genetic linkage maps with potential applications in plant breeding. The newly available fully sequenced plant genomes represent an incredible opportunity for comparative analyses that may reveal new aspects of genome biology and evolution. The analysis of the expansion and evolution of gene families across species is a common approach to infer biological functions. To date, the extent and role of gene families in plants has only been partially addressed and many gene families remain to be investigated. Manual identification of gene families is highly time-consuming and laborious, requiring an iterative process of manual and computational analysis to identify members of a given family, typically combining numerous BLAST searches and manually cleaning data. Due to the increasing abundance of genome sequences and the agronomical interest in plant gene families, the field needs a clear, automated annotation tool.ResultsHere, we present the geneHummus package, an R-based pipeline for the identification and characterization of plant gene families. The impact of this pipeline comes from a reduction in hands-on annotation time combined with high specificity and sensitivity in extracting only proteins from the RefSeq database and providing the conserved domain architectures based on SPARCLE. As a case study we focused on the auxin receptor factors gene (ARF) family in Cicer arietinum (chickpea) and other legumes.ConclusionWe anticipate that our pipeline should be suitable for any taxonomic plant family, and likely other gene families, vastly improving the speed and ease of genomic data processing.

Construction of an integrated genetic linkage map and detection of quantitative trait loci for ascochyta blight resistance in faba bean (Vicia faba L.)

Ascochyta blight (AB), caused by Ascochyta fabae Speg., is an economically important disease that has been reported in most of the faba bean growing regions worldwide. Breeding for resistance is the most environmentally acceptable and economically feasible method to address the disease, for which a detailed understanding of the genetic basis of AB resistance is required. In the current study, a genetic linkage map based on single nucleotide polymorphisms was developed from Nura × Farah recombinant inbred line (RIL) population and contained 705 loci across 1021.8 cM. The marker information from Nura × Farah map was combined with previously published maps to generate an integrated map consisting of 1850 markers distributed across six linkage groups, with a cumulative length of 1439 cM at an average density of one marker per 0.80 cM. Parents and RIL progeny were screened for AB with two strains of A. fabae and quantitative trait locus analysis identified two genomic regions explaining up to 49% of the phenotypic variation. Evaluation of linked markers in a diverse set of faba bean genotypes validated their utility for marker assisted selection. The availability of high density genetic linkage map along with the linked markers for AB resistance provides opportunities for genomics-assisted breeding, map based gene isolation and comparative genetics in faba bean.

A High-Density Genetic Map of an Allohexaploid Brassica Doubled Haploid Population Reveals Quantitative Trait Loci for Pollen Viability and Fertility.

A doubled haploid (DH) mapping population was obtained from microspore culture of an allohexaploid F1 from the cross between two recently-synthesized allohexaploid Brassica lines. We used single nucleotide polymorphism (SNP) genetic variation based on restriction-site associated DNA (RAD) sequencing to construct a high density genetic linkage map of the population. RAD libraries were constructed from the genomic DNA of both parents and 146 DH progenies. A total of 2.87 G reads with an average sequencing depth of 2.59 × were obtained in the parents and of 1.41 × in the progeny. A total of 290,422 SNPs were identified from clustering of RAD reads, from which we developed 7,950 high quality SNP markers that segregated normally (1:1) in the population. The linkage map contained all 27 chromosomes from the parental A, B and C genomes with a total genetic distance of 5725.19 cM and an average of 0.75 cM between adjacent markers. Genetic distance on non-integrated linkage groups was 1534.23 cM, or 21% of total genetic distance. Out of 146 DH progenies, 91 had a complete set of 27 chromosomes as expected of a hexaploid species, and 21 out of 27 chromosomes showed high collinearity between the physical and linkage maps. The loss of chromosome(s) or chromosome segment(s) in the DH population was associated with a reduction in pollen viability. Twenty-five additive QTL were associated with pollen viability and fertility-related traits (seed number, seed yield, pod length, plant height, 1000-seed weight). In addition, 44 intra-genomic and 18 inter-genomic epistatic QTL pairs were detected for 4 phenotypic traits. This provides confidence that the DH population may be selected for improved pollen viability and fertility in a future allohexaploid Brassica species.

Accounting for Errors in Low Coverage High-Throughput Sequencing Data When Constructing Genetic Maps Using Biparental Outcrossed Populations.

Next-generation sequencing is an efficient method that allows for substantially more markers than previous technologies, providing opportunities for building high-density genetic linkage maps, which facilitate the development of nonmodel species' genomic assemblies and the investigation of their genes. However, constructing genetic maps using data generated via high-throughput sequencing technology (e.g., genotyping-by-sequencing) is complicated by the presence of sequencing errors and genotyping errors resulting from missing parental alleles due to low sequencing depth. If unaccounted for, these errors lead to inflated genetic maps. In addition, map construction in many species is performed using full-sibling family populations derived from the outcrossing of two individuals, where unknown parental phase and varying segregation types further complicate construction. We present a new methodology for modeling low coverage sequencing data in the construction of genetic linkage maps using full-sibling populations of diploid species, implemented in a package called GUSMap. Our model is based on the Lander-Green hidden Markov model but extended to account for errors present in sequencing data. We were able to obtain accurate estimates of the recombination fractions and overall map distance using GUSMap, while most existing mapping packages produced inflated genetic maps in the presence of errors. Our results demonstrate the feasibility of using low coverage sequencing data to produce genetic maps without requiring extensive filtering of potentially erroneous genotypes, provided that the associated errors are correctly accounted for in the model.

A SNP-Based Genetic Linkage Map of Soybean Using the SoySNP6K Illumina Infinium BeadChip Genotyping Array

This study reports a high density genetic linkage map based on the ‘Maryland 96-5722’ by ‘Spencer’ recombinant inbred line (RIL) population of soybean [Glycine max (L.) Merr.] and constructed exclusively with single nucleotide polymorphism (SNP) markers. The Illumina Infinium SoySNP6K BeadChip genotyping array produced 5,376 SNPs in the mapping population, with a 96.75% success rate. Significant level of goodness-of-fit for each locus was tested based on the observed vs. expected ratio (1:1). Out of 5,376 markers, 1,465 SNPs fit the 1:1 segregation rate having ≤20% missing data plus heterozygosity among the RILs. Among this 1,456 just 657 were polymorphic between the parents DNAs tested. These 657 SNPs were mapped using the JoinMap 4.0 software and 550 SNPs were distributed on 16 linkage groups (LGs) among the 20 chromosomes of the soybean genome. The total map length was just 201.57 centiMorgans (cM) with an average marker density of 0.37 cM. This is one of the high density SNP-based genetic linkage maps of soybean that will be used by the scientific community to map quantitative trait loci (QTL) and identify candidate genes for important agronomic traits in soybean.

Fine Mapping of QTLs for Ascochyta Blight Resistance in Pea Using Heterogeneous Inbred Families.

Ascochyta blight (AB) is an important disease of pea which can cause severe grain yield loss under wet conditions. In our previous study, we identified two quantitative trait loci (QTLs) abIII-1 and abI-IV-2 for AB resistance and these QTLs were consistent across locations and/or years in an inter-specific pea population (PR-19) developed from a cross between Alfetta (Pisum sativum) and P651 (P. fulvum). The objectives of this study were to fine map the abIII-1 and abI-IV-2 QTLs using a high density single nucleotide polymorphism (SNP)-based genetic linkage map and analyze identified markers in heterogeneous inbred family (HIF) populations. Selective genotyping of 51 PR-19 recombinant inbred lines was performed using genotyping-by-sequencing (GBS) and the resulting high density genetic linkage map was used to identify eight new SNP markers within the abI-IV-2 QTL, whereas no additional SNPs were identified within the abIII-1 QTL. Two HIF populations HIF-224 (143 lines) and HIF-173 (126 lines) were developed from F6 RILs PR-19-224 and PR-19-173, respectively. The HIF populations evaluated under field conditions in 2015 and 2016 showed a wide range of variation for reaction to AB resistance. Lodging score had significant positive (P < 0.001) correlation with AB scores. HIFs were genotyped using SNP markers within targeted QTLs. The genotypic and phenotypic data of the HIFs were used to identify two new QTLs, abI-IV-2.1 and abI-IV-2.2 for AB resistance within the abI-IV-2 QTL. These QTLs individually explained 5.5 to 14% of the total phenotypic variation. Resistance to lodging was also associated with these two QTLs. Identified SNP markers will be useful in marker assisted selection for development of pea cultivars with improved AB resistance.

Development of high-density interspecific genetic maps for the identification of QTLs conferring resistance to Valsa ceratosperma in apple

Valsa canker (Valsa ceratosperma (Tode ex Fr.) Maire) is one of the most destructive fungal diseases of apple, especially in Eastern Asia. In this study, the first high density genetic linkage map of Malus asiatica × Malus domestica was constructed by 640 simple sequence repeats (SSRs) and 490 single nucleotide polymorphisms (SNPs), which spanned 1497.5 cM with an average marker interval of 1.33 cM per marker. Quantitative trait loci (QTLs) for apple’s resistance to V. ceratosperma isolates 03-8 and xc56 were identified using the linkage map. Lesion lengths were used as the phenotypic data for the QTL analysis, which were measured on 1-year-old shoots inoculated with conidia of the two isolates. One QTL for resistance to isolate 03-8 was mapped on LG 16, and one QTL for resistance to isolate xc56 was detected on LG 9. Our research not only promoted the further understanding of the genetic basis of apple’s resistance to Valsa canker but also provided two molecular markers that might be used in future marker-assisted selection for resistance in apple breeding programs.

QTL underlying some agronomic traits in barley detected by SNP markers.

BackgroundIncreasing the yield of barley (Hordeum vulgare L.) is a main breeding goal in developing barley cultivars. A high density genetic linkage map containing 1894 SNP and 68 SSR markers covering 1375.8 cM was constructed and used for mapping quantitative traits. A late-generation double haploid population (DH) derived from the Huaai 11 × Huadamai 6 cross was used to identify QTLs and QTL × environment interactions for ten traits affecting grain yield including length of main spike (MSL), spikelet number on main spike (SMS), spikelet number per plant (SLP), grain number per plant (GP), grain weight per plant (GWP), grain number per spike (GS), thousand grain weight (TGW), grain weight per spike (GWS), spike density (SPD) and spike number per plant (SP).ResultsIn single environment analysis using composite interval mapping (CIM), a total of 221 QTLs underlying the ten traits were detected in five consecutive years (2009–2013). The QTLs detected in each year were 50, 48, 41, 41 and 41 for the year 2009 to 2013. The QTLs associated with these traits were generally clustered on chromosome 2H, 4H and 7H.In multi-environment analysis, a total of 111 significant QTLs including 18 for MSL, 16 for SMS, 15 for SPD, 5 for SP, 4 for SLP, 14 for TGW, 5 for GP, 11 for GS, 8 for GWP, and 15 for GWS were detected in the five years. Most QTLs showed significant QTL × environment interactions (QEI), nine QTLs (qIMSL3-1, qIMSL4-1, qIMSL4-2, qIMSL6-1, qISMS7-1, qISPD2-7, qISPD7-1, qITGW3-1 and qIGWS4-3) were detected with minimal QEI effects and stable in different years. Among 111 QTLs,71 (63.40 %) QTLs were detected in both single and multiple environments.ConclusionsThree main QTL cluster regions associated with the 10 agronomic traits on chromosome 2H, 4H and 7H were detected. The QTLs for SMS, SLP, GP and GWP were located in the region near Vrs1 on chromosome 2H. The QTLs underlying SMS, SPD and SLP were clustered on chromosome 4H. On the terminal of chromosome 7H, there was a QTL cluster associated with TGW, SPD, GWP and GWS. The information will be useful for marker-assisted selection (MAS) in barley breeding.Electronic supplementary materialThe online version of this article (doi:10.1186/s12863-016-0409-y) contains supplementary material, which is available to authorized users.

An ultra-high density genetic linkage map of perennial ryegrass (Lolium perenne) using genotyping by sequencing (GBS) based on a reference shotgun genome assembly.

High density genetic linkage maps that are extensively anchored to assembled genome sequences of the organism in question are extremely useful in gene discovery. To facilitate this process in perennial ryegrass (Lolium perenne L.), a high density single nucleotide polymorphism (SNP)- and presence/absence variant (PAV)-based genetic linkage map has been developed in an F2 mapping population that has been used as a reference population in numerous studies. To provide a reference sequence to which to align genotyping by sequencing (GBS) reads, a shotgun assembly of one of the grandparents of the population, a tenth-generation inbred line, was created using Illumina-based sequencing. The assembly was based on paired-end Illumina reads, scaffolded by mate pair and long jumping distance reads in the range of 3-40 kb, with >200-fold initial genome coverage. A total of 169 individuals from an F2 mapping population were used to construct PstI-based GBS libraries tagged with unique 4-9 nucleotide barcodes, resulting in 284 million reads, with approx. 1·6 million reads per individual. A bioinformatics pipeline was employed to identify both SNPs and PAVs. A core genetic map was generated using high confidence SNPs, to which lower confidence SNPs and PAVs were subsequently fitted in a straightforward binning approach. The assembly comprises 424 750 scaffolds, covering 1·11 Gbp of the 2·5 Gbp perennial ryegrass genome, with a scaffold N50 of 25 212 bp and a contig N50 of 3790 bp. It is available for download, and access to a genome browser has been provided. Comparison of the assembly with available transcript and gene model data sets for perennial ryegrass indicates that approx. 570 Mbp of the gene-rich portion of the genome has been captured. An ultra-high density genetic linkage map with 3092 SNPs and 7260 PAVs was developed, anchoring just over 200 Mb of the reference assembly. The combined genetic map and assembly, combined with another recently released genome assembly, represent a significant resource for the perennial ryegrass genetics community.

An ultra-high density linkage map and QTL mapping for sex and growth-related traits of common carp (Cyprinus carpio).

High density genetic linkage maps are essential for QTL fine mapping, comparative genomics and high quality genome sequence assembly. In this study, we constructed a high-density and high-resolution genetic linkage map with 28,194 SNP markers on 14,146 distinct loci for common carp based on high-throughput genotyping with the carp 250 K single nucleotide polymorphism (SNP) array in a mapping family. The genetic length of the consensus map was 10,595.94 cM with an average locus interval of 0.75 cM and an average marker interval of 0.38 cM. Comparative genomic analysis revealed high level of conserved syntenies between common carp and the closely related model species zebrafish and medaka. The genome scaffolds were anchored to the high-density linkage map, spanning 1,357 Mb of common carp reference genome. QTL mapping and association analysis identified 22 QTLs for growth-related traits and 7 QTLs for sex dimorphism. Candidate genes underlying growth-related traits were identified, including important regulators such as KISS2, IGF1, SMTLB, NPFFR1 and CPE. Candidate genes associated with sex dimorphism were also identified including 3KSR and DMRT2b. The high-density and high-resolution genetic linkage map provides an important tool for QTL fine mapping and positional cloning of economically important traits, and improving common carp genome assembly.

Construction of high resolution genetic linkage maps to improve the soybean genome sequence assembly Glyma1.01.

BackgroundA landmark in soybean research, Glyma1.01, the first whole genome sequence of variety Williams 82 (Glycine max L. Merr.) was completed in 2010 and is widely used. However, because the assembly was primarily built based on the linkage maps constructed with a limited number of markers and recombinant inbred lines (RILs), the assembled sequence, especially in some genomic regions with sparse numbers of anchoring markers, needs to be improved. Molecular markers are being used by researchers in the soybean community, however, with the updating of the Glyma1.01 build based on the high-resolution linkage maps resulting from this research, the genome positions of these markers need to be mapped.ResultsTwo high density genetic linkage maps were constructed based on 21,478 single nucleotide polymorphism loci mapped in the Williams 82 x G. soja (Sieb. & Zucc.) PI479752 population with 1083 RILs and 11,922 loci mapped in the Essex x Williams 82 population with 922 RILs. There were 37 regions or single markers where marker order in the two populations was in agreement but was not consistent with the physical position in the Glyma1.01 build. In addition, 28 previously unanchored scaffolds were positioned. Map data were used to identify false joins in the Glyma1.01 assembly and the corresponding scaffolds were broken and reassembled to the new assembly, Wm82.a2.v1. Based upon the plots of the genetic on physical distance of the loci, the euchromatic and heterochromatic regions along each chromosome in the new assembly were delimited. Genomic positions of the commonly used markers contained in BARCSOYSSR_1.0 database and the SoySNP50K BeadChip were updated based upon the Wm82.a2.v1 assembly.ConclusionsThe information will facilitate the study of recombination hot spots in the soybean genome, identification of genes or quantitative trait loci controlling yield, seed quality and resistance to biotic or abiotic stresses as well as other genetic or genomic research.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-015-2344-0) contains supplementary material, which is available to authorized users.

A genetic linkage map with 178 SSR and 1 901 SNP markers constructed using a RIL population in wheat (Triticum aestivum L.)

The construction of high density genetic linkage map provides a powerful tool to detect and map quantitative trait loci (QTLs) controlling agronomically important traits. In this study, simple sequence repeat (SSR) markers and Illumina 9K iSelect single nucleotide polymorphism (SNP) genechip were employed to construct one genetic linkage map of common wheat (Triticum aestivum L.) using 191 recombinant inbred lines (RILs) derived from cross Yu 8679×Jing 411. This map included 1 901 SNP loci and 178 SSR loci, covering 1 659.9 cM and 1 000 marker bins, with an average interval distance of 1.66 cM. A, B and D genomes covered 719.1, 703.5 and 237.3 cM, with an average interval distance of 1.66, 1.45 and 2.9 cM, respectively. Notably, the genetic linkage map covered 20 chromosomes, with the exception of chromosome 5D. Bioinformatics analysis revealed that 1 754 (92.27%) of 1 901 mapped SNP loci could be aligned to 1 215 distinct wheat unigenes, among which 1 184 (97.4%) were located on one single chromosome, and the rest 31 (2.6%) were located on 2 to 3 chromosomes. By performing in silico comparison, 214 chromosome deletion bin-mapped expressed sequence tags (ESTs), 1 043 Brachypodium genes and 1 033 rice genes were further added onto the genetic linkage map. This map not only integrated genetic and physical maps, SSR and SNP loci, respectively, but also provided the information of Brachypodium and rice genes corresponding to 1 754 SNP loci. Therefore, it will be a useful tool for comparative genomics analysis, fine mapping of QTL/gene controlling agronomically important traits and marker-assisted selection breeding in wheat.