Computational approaches and software tools for genetic linkage map estimation in plants

Discovery and validation of SSR marker-based QTL governing fresh pod yield in dolichos bean (Lablab purpureus L. Sweet)

Identification and validation of quantitative trait loci (QTL) governing desired phenotype of target trait is a prerequisite to implement marker-assisted selection in any crop including dolichos bean. Under this premise, we used two mapping populations (MPs) to detect and cross population validate QTL controlling fresh pod yield. One of the MPs consisted of F2 individuals (MP1) derived from crossing two elite genotypes, the second MP consisted of random RILs (MP2) derived from a different pair of elite genotypes. The MP1 and MP2 were genotyped using polymorphic 86 and 91 SSR markers, respectively and linkage maps were constructed using QTL IciM mapping software. The MP1 and MP2 were phenotyped during 2021 and 2017 rainy and post rainy seasons, respectively for fresh pod yield plant-1 following two-replicated simple lattice design. QTL maps were developed in MP1 and MP2 using genotype and phenotype data. Our results indicated that the estimates of total map length, average map length per linkage group (LG) and average inter-marker distance in MP2 were greater (by at least 1.5 times) than those in MP1. While seven QTLs were detected in MP1, six were detected in MP2 with three QTL exhibiting positive and additive minor effects for fresh pod yield plant-1. We also detected one common minor positive effect QTL across two seasons in MP2 and significant epistatic QTL, whose main effects were non-significant. One each of the seven and six QTL-linked SSR markers detected in MP1 and MP2, respectively were cross-population validated. The implications of these results are discussed in relation to strategies to breed dolichos bean.

Smooth Descent: A ploidy-aware algorithm to improve linkage mapping in the presence of genotyping errors

Linkage mapping is an approach to order markers based on recombination events. Mapping algorithms cannot easily handle genotyping errors, which are common in high-throughput genotyping data. To solve this issue, strategies have been developed, aimed mostly at identifying and eliminating these errors. One such strategy is SMOOTH, an iterative algorithm to detect genotyping errors. Unlike other approaches, SMOOTH can also be used to impute the most probable alternative genotypes, but its application is limited to diploid species and to markers heterozygous in only one of the parents. In this study we adapted SMOOTH to expand its use to any marker type and to autopolyploids with the use of identity-by-descent probabilities, naming the updated algorithm Smooth Descent (SD). We applied SD to real and simulated data, showing that in the presence of genotyping errors this method produces better genetic maps in terms of marker order and map length. SD is particularly useful for error rates between 5% and 20% and when error rates are not homogeneous among markers or individuals. With a starting error rate of 10%, SD reduced it to ∼5% in diploids, ∼7% in tetraploids and ∼8.5% in hexaploids. Conversely, the correlation between true and estimated genetic maps increased by 0.03 in tetraploids and by 0.2 in hexaploids, while worsening slightly in diploids (∼0.0011). We also show that the combination of genotype curation and map re-estimation allowed us to obtain better genetic maps while correcting wrong genotypes. We have implemented this algorithm in the R package Smooth Descent.

Identification and genomic characterization of major effect bacterial blight resistance locus (BB-13) in Upland cotton (Gossypium hirsutum L.)

Identification and genomic characterization of major resistance locus against cotton bacterial blight (CBB) using GWAS and linkage mapping to enable genomics-based development of durable CBB resistance and gene discovery in cotton. Cotton bacterial leaf blight (CBB), caused by Xanthomonas citri subsp. malvacearum (Xcm), has periodically been a damaging disease in the USA. Identification and deployment of genetic resistance in cotton cultivars is the most economical and efficient means of reducing crop losses due to CBB. In the current study, genome-wide association study (GWAS) of CBB resistance using an elite diversity panel of 380 accessions, genotyped with the cotton single nucleotide polymorphism (SNP) 63 K array, and phenotyped with race-18 of CBB, localized the CBB resistance to a 2.01-Mb region in the long arm of chromosome D02. Molecular genetic mapping using an F₆ recombinant inbred line (RIL) population showed the CBB resistance in cultivar Arkot 8102 was controlled by a single locus (BB-13). The BB-13 locus was mapped within the 0.95-cM interval near the telomeric region in the long arm of chromosome D02. Flanking SNP markers, i04890Gh and i04907Gh of the BB-13 locus, identified from the combined linkage analysis and GWAS, targeted it to a 371-Kb genomic region. Candidate gene analysis identified thirty putative gene sequences in the targeted genomic region. Nine of these putative genes and two NBS-LRR genes adjacent to the targeted region were putatively involved in plant disease resistance and are possible candidate genes for BB-13 locus. Genetic mapping and genomic targeting of the BB13 locus in the current study will help in cloning the CBB-resistant gene and establishing the molecular genetic architecture of the BB-13 locus towards developing durable resistance to CBB in cotton.

SeSAM: software for automatic construction of order-robust linkage maps

Background

Genotyping and sequencing technologies produce increasingly large numbers of genetic markers with potentially high rates of missing or erroneous data. Therefore, the construction of linkage maps is more and more complex. Moreover, the size of segregating populations remains constrained by cost issues and is less and less commensurate with the numbers of SNPs available. Thus, guaranteeing a statistically robust marker order requires that maps include only a carefully selected subset of SNPs.

Results

In this context, the SeSAM software allows automatic genetic map construction using seriation and placement approaches, to produce (1) a high-robustness framework map which includes as many markers as possible while keeping the order robustness beyond a given statistical threshold, and (2) a high-density total map including the framework plus almost all polymorphic markers. During this process, care is taken to limit the impact of genotyping errors and of missing data on mapping quality. SeSAM can be used with a wide range of biparental populations including from outcrossing species for which phases are inferred on-the-fly by maximum-likelihood during map elongation. The package also includes functions to simulate data sets, convert data formats, detect putative genotyping errors, visualize data and map quality (including graphical genotypes), and merge several maps into a consensus. SeSAM is also suitable for interactive map construction, by providing lower-level functions for 2-point and multipoint EM analyses. The software is implemented in a R package including functions in C++.

Conclusions

SeSAM is a fully automatic linkage mapping software designed to (1) produce a framework map as robust as desired by optimizing the selection of a subset of markers, and (2) produce a high-density map including almost all polymorphic markers. The software can be used with a wide range of biparental mapping populations including cases from outcrossing. SeSAM is freely available under a GNU GPL v3 license and works on Linux, Windows, and macOS platforms. It can be downloaded together with its user-manual and quick-start tutorial from ForgeMIA (SeSAM project) at https://forgemia.inra.fr/gqe-acep/sesam/-/releases

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-022-05045-7.

Physical mapping of QTL associated with agronomic and end-use quality traits in spring wheat under conventional and organic management systems

Using phenotypic data of four biparental spring wheat populations evaluated at multiple environments under two management systems, we discovered 152 QTL and 22 QTL hotspots, of which two QTL accounted for up to 37% and 58% of the phenotypic variance, consistently detected in all environments, and fell within genomic regions harboring known genes. Identification of the physical positions of quantitative trait loci (QTL) would be highly useful for developing functional markers and comparing QTL results across multiple independent studies. The objectives of the present study were to map and characterize QTL associated with nine agronomic and end-use quality traits (tillering ability, plant height, lodging, grain yield, grain protein content, thousand kernel weight, test weight, sedimentation volume, and falling number) in hard red spring wheat recombinant inbred lines (RILs) using the International Wheat Genome Sequencing Consortium (IWGSC) RefSeq v2.0 physical map. We evaluated a total of 698 RILs from four populations derived from crosses involving seven parents at 3-8 conventionally (high N) and organically (low N) managed field environments. Using the phenotypic data combined across all environments per management, and the physical map between 1058 and 6526 markers per population, we identified 152 QTL associated with the nine traits, of which 29 had moderate and 2 with major effects. Forty-nine of the 152 QTL mapped across 22 QTL hotspot regions with each region coincident to 2-6 traits. Some of the QTL hotspots were physically located close to known genes. QSv.dms-1A and QPht.dms-4B.1 individually explained up to 37% and 58% of the variation in sedimentation volume and plant height, respectively, and had very large LOD scores that varied from 19.0 to 35.7 and from 16.7 to 55.9, respectively. We consistently detected both QTL in the combined and all individual environments, laying solid ground for further characterization and possibly for cloning.

Characterization of black spot resistance in diploid roses with QTL detection, meta-analysis and candidate-gene identification

Two environmentally stable QTLs linked to black spot disease resistance in the Rosa wichurana genetic background were detected, in different connected populations, on linkage groups 3 and 5. Co-localization between R-genes and defense response genes was revealed via meta-analysis. The widespread rose black spot disease (BSD) caused by the hemibiotrophic fungus Diplocarpon rosae Wolf. is efficiently controlled with fungicides. However, in the actual context of reducing agrochemical use, the demand for rose bushes with higher levels of resistance has increased. Qualitative resistance conferred by major genes (Rdr genes) has been widely studied but quantitative resistance to BSD requires further investigation. In this study, segregating populations connected through the BSD resistant Rosa wichurana male parent were phenotyped for disease resistance over several years and locations. A pseudo-testcross approach was used, resulting in six parental maps across three populations. A total of 45 individual QTLs with significant effect on BSD resistance were mapped on the male maps (on linkage groups (LG) B3, B4, B5 and B6), and 12 on the female maps (on LG A1, A2, A3, A4 and A5). Two major regions linked to BSD resistance were identified on LG B3 and B5 of the male maps and were integrated into a consensus map built from all three of the male maps. A meta-analysis was used to narrow down the confidence intervals of individual QTLs from three populations by generating meta-QTLs. Two 'hot spots' or meta-QTLs were found per LG, enabling reduction of the confidence interval to 10.42 cM for B3 and 11.47 cM for B5. An expert annotation of NBS-LRR encoding genes of the genome assembly of Hibrand et al. was performed and used to explore potential co-localization with R-genes. Co-localization with defense response genes was also investigated.

Unraveling the Hexaploid Sweetpotato Inheritance Using Ultra-Dense Multilocus Mapping

The hexaploid sweetpotato (Ipomoea batatas (L.) Lam., 2n = 6x = 90) is an important staple food crop worldwide and plays a vital role in alleviating famine in developing countries. Due to its high ploidy level, genetic studies in sweetpotato lag behind major diploid crops significantly. We built an ultra-dense multilocus integrated genetic map and characterized the inheritance system in a sweetpotato full-sib family using our newly developed software, MAPpoly. The resulting genetic map revealed 96.5% collinearity between I. batatas and its diploid relative I. trifida We computed the genotypic probabilities across the whole genome for all individuals in the mapping population and inferred their complete hexaploid haplotypes. We provide evidence that most of the meiotic configurations (73.3%) were resolved in bivalents, although a small portion of multivalent signatures (15.7%), among other inconclusive configurations (11.0%), were also observed. Except for low levels of preferential pairing in linkage group 2, we observed a hexasomic inheritance mechanism in all linkage groups. We propose that the hexasomic-bivalent inheritance promotes stability to the allelic transmission in sweetpotato.

Unraveling the Hexaploid Sweetpotato Inheritance Using Ultra-Dense Multilocus Mapping

The hexaploid sweetpotato (Ipomoea batatas (L.) Lam., 2n = 6x = 90) is an important staple food crop worldwide and plays a vital role in alleviating famine in developing countries. Due to its high ploidy level, genetic studies in sweetpotato lag behind major diploid crops significantly. We built an ultra-dense multilocus integrated genetic map and characterized the inheritance system in a sweetpotato full-sib family using our newly developed software, MAPpoly. The resulting genetic map revealed 96.5% collinearity between I. batatas and its diploid relative I. trifida We computed the genotypic probabilities across the whole genome for all individuals in the mapping population and inferred their complete hexaploid haplotypes. We provide evidence that most of the meiotic configurations (73.3%) were resolved in bivalents, although a small portion of multivalent signatures (15.7%), among other inconclusive configurations (11.0%), were also observed. Except for low levels of preferential pairing in linkage group 2, we observed a hexasomic inheritance mechanism in all linkage groups. We propose that the hexasomic-bivalent inheritance promotes stability to the allelic transmission in sweetpotato.

Construction of a genetic linkage map in Pyropia yezoensis (Bangiales, Rhodophyta) and QTL analysis of several economic traits of blades

Pyropia yezoensis is an economically important seaweed but its molecular genetics is poorly understood. In the present study, we used a doubled haploid (DH) population that was established in our previous work to construct a genetic linkage map of P. yezoensis and analyze the quantitative trait loci (QTLs) of blades. The DH population was genotyped with fluorescent sequence-related amplified polymorphism (SRAP) markers. A chi-square test identified 301 loci with normal segregation (P ≥ 0.01) and 96 loci (24.18%) with low-level skewed segregation (0.001 ≤ P < 0.01). The genetic map was constructed after a total of 92 loci were assembled into three linkage groups (LGs). The map spanned 557.36 cM covering 93.71% of the estimated genome, with a mean interlocus space of 6.23 cM. Kolmogorov-Smirnov test (α = 5%) showed a uniform distribution of the markers along each LG. On the genetic map, 10 QTLs associated with five economic traits of blades were detected. One QTL was for length, one for width, two for fresh weight, two for specific growth rate of length and four for specific growth rate of fresh weight. These QTLs could explain 2.29–7.87% of the trait variations, indicating that their effects were all minor. The results may serve as a framework for future marker-assisted breeding in P. yezoensis.

Estimation of Recombination Rate and Maternal Linkage Disequilibrium in Half-Sibs

A livestock population can be characterized by different population genetic parameters, such as linkage disequilibrium and recombination rate between pairs of genetic markers. The population structure, which may be caused by family stratification, has an influence on the estimates of these parameters. An expectation maximization algorithm has been proposed for estimating these parameters in half-sibs without phasing the progeny. It, however, overlooks the fact that the underlying likelihood function may have two maxima. The magnitudes of the maxima depend on the maternal allele frequencies at the investigated marker pair. Which maximum the algorithm converges to depends on the chosen start values. We present a stepwise procedure in which the relationship between the two modes is exploited. The expectation maximization algorithm for the parameter estimation is applied twice using different start values, followed by a decision process to assess the most likely estimate. This approach was validated using simulated genotypes of half-sibs. It was also applied to a dairy cattle dataset consisting of multiple half-sib families and 39,780 marker genotypes, leading to estimates for 12,759,713 intrachromosomal marker pairs. Furthermore, the proper order of markers was verified by studying the mean of estimated recombination rates in a window adjacent to the investigated locus as well as in a window at its most distant chromosome end. Putatively misplaced markers or marker clusters were detected by comparing the results with the revised bovine genome assembly UMD 3.1.1. In total, 40 markers were identified as candidates of misplacement. This outcome may help improving the physical order of markers which is also required for refining the bovine genetic map.

Tools for Genetic Studies in Experimental Populations of Polyploids

Polyploid organisms carry more than two copies of each chromosome, a condition rarely tolerated in animals but which occurs relatively frequently in the plant kingdom. One of the principal challenges faced by polyploid organisms is to evolve stable meiotic mechanisms to faithfully transmit genetic information to the next generation upon which the study of inheritance is based. In this review we look at the tools available to the research community to better understand polyploid inheritance, many of which have only recently been developed. Most of these tools are intended for experimental populations (rather than natural populations), facilitating genomics-assisted crop improvement and plant breeding. This is hardly surprising given that a large proportion of domesticated plant species are polyploid. We focus on three main areas: (1) polyploid genotyping; (2) genetic and physical mapping; and (3) quantitative trait analysis and genomic selection. We also briefly review some miscellaneous topics such as the mode of inheritance and the availability of polyploid simulation software. The current polyploid analytic toolbox includes software for assigning marker genotypes (and in particular, estimating the dosage of marker alleles in the heterozygous condition), establishing chromosome-scale linkage phase among marker alleles, constructing (short-range) haplotypes, generating linkage maps, performing genome-wide association studies (GWAS) and quantitative trait locus (QTL) analyses, and simulating polyploid populations. These tools can also help elucidate the mode of inheritance (disomic, polysomic or a mixture of both as in segmental allopolyploids) or reveal whether double reduction and multivalent chromosomal pairing occur. An increasing number of polyploids (or associated diploids) are being sequenced, leading to publicly available reference genome assemblies. Much work remains in order to keep pace with developments in genomic technologies. However, such technologies also offer the promise of understanding polyploid genomes at a level which hitherto has remained elusive.

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.

TSPmap, a tool making use of traveling salesperson problem solvers in the efficient and accurate construction of high-density genetic linkage maps

Background

Recent advances in nucleic acid sequencing technologies have led to a dramatic increase in the number of markers available to generate genetic linkage maps. This increased marker density can be used to improve genome assemblies as well as add much needed resolution for loci controlling variation in ecologically and agriculturally important traits. However, traditional genetic map construction methods from these large marker datasets can be computationally prohibitive and highly error prone.

Results

We present TSPmap, a method which implements both approximate and exact Traveling Salesperson Problem solvers to generate linkage maps. We demonstrate that for datasets with large numbers of genomic markers (e.g. 10,000) and in multiple population types generated from inbred parents, TSPmap can rapidly produce high quality linkage maps with low sensitivity to missing and erroneous genotyping data compared to two other benchmark methods, JoinMap and MSTmap. TSPmap is open source and freely available as an R package.

Conclusions

With the advancement of low cost sequencing technologies, the number of markers used in the generation of genetic maps is expected to continue to rise. TSPmap will be a useful tool to handle such large datasets into the future, quickly producing high quality maps using a large number of genomic markers.

Electronic supplementary material

The online version of this article (10.1186/s13040-017-0158-0) contains supplementary material, which is available to authorized users.

Effect of Co-segregating Markers on High-Density Genetic Maps and Prediction of Map Expansion Using Machine Learning Algorithms

Advances in sequencing and genotyping methods have enable cost-effective production of high throughput single nucleotide polymorphism (SNP) markers, making them the choice for linkage mapping. As a result, many laboratories have developed high-throughput SNP assays and built high-density genetic maps. However, the number of markers may, by orders of magnitude, exceed the resolution of recombination for a given population size so that only a minority of markers can accurately be ordered. Another issue attached to the so-called 'large p, small n' problem is that high-density genetic maps inevitably result in many markers clustering at the same position (co-segregating markers). While there are a number of related papers, none have addressed the impact of co-segregating markers on genetic maps. In the present study, we investigated the effects of co-segregating markers on high-density genetic map length and marker order using empirical data from two populations of wheat, Mohawk × Cocorit (durum wheat) and Norstar × Cappelle Desprez (bread wheat). The maps of both populations consisted of 85% co-segregating markers. Our study clearly showed that excess of co-segregating markers can lead to map expansion, but has little effect on markers order. To estimate the inflation factor (IF), we generated a total of 24,473 linkage maps (8,203 maps for Mohawk × Cocorit and 16,270 maps for Norstar × Cappelle Desprez). Using seven machine learning algorithms, we were able to predict with an accuracy of 0.7 the map expansion due to the proportion of co-segregating markers. For example in Mohawk × Cocorit, with 10 and 80% co-segregating markers the length of the map inflated by 4.5 and 16.6%, respectively. Similarly, the map of Norstar × Cappelle Desprez expanded by 3.8 and 11.7% with 10 and 80% co-segregating markers. With the increasing number of markers on SNP-chips, the proportion of co-segregating markers in high-density maps will continue to increase making map expansion unavoidable. Therefore, we suggest developers improve linkage mapping algorithms for efficient analysis of high-throughput data. This study outlines a practical strategy to estimate the IF due to the proportion of co-segregating markers and outlines a method to scale the length of the map accordingly.

A high-resolution reference genetic map positioning 8.8 K genes for the conifer white spruce: structural genomics implications and correspondence with physical distance

Over the last decade, extensive genetic and genomic resources have been developed for the conifer white spruce (Picea glauca, Pinaceae), which has one of the largest plant genomes (20 Gbp). Draft genome sequences of white spruce and other conifers have recently been produced, but dense genetic maps are needed to comprehend genome macrostructure, delineate regions involved in quantitative traits, complement functional genomic investigations, and assist the assembly of fragmented genomic sequences. A greatly expanded P. glauca composite linkage map was generated from a set of 1976 full-sib progeny, with the positioning of 8793 expressed genes. Regions with significant low or high gene density were identified. Gene family members tended to be mapped on the same chromosomes, with tandemly arrayed genes significantly biased towards specific functional classes. The map was integrated with transcriptome data surveyed across eight tissues. In total, 69 clusters of co-expressed and co-localising genes were identified. A high level of synteny was found with pine genetic maps, which should facilitate the transfer of structural information in the Pinaceae. Although the current white spruce genome sequence remains highly fragmented, dozens of scaffolds encompassing more than one mapped gene were identified. From these, the relationship between genetic and physical distances was examined and the genome-wide recombination rate was found to be much smaller than most estimates reported for angiosperm genomes. This gene linkage map shall assist the large-scale assembly of the next-generation white spruce genome sequence and provide a reference resource for the conifer genomics community.

The potential of probabilistic graphical models in linkage map construction

Probabilistic graphical models show great potential for robust and reliable construction of linkage maps. We show how to use probabilistic graphical models to construct high-quality linkage maps in the face of data perturbations caused by genotyping errors and reciprocal translocations. It has been shown that linkage map construction can be hampered by the presence of genotyping errors and chromosomal rearrangements such as inversions and translocations. Here, we report a novel method for linkage map construction using probabilistic graphical models. The method is proven, both theoretically and practically, to be effective in filtering out markers that contain genotyping errors. In particular, it carries out marker filtering and ordering simultaneously, and is therefore superior to the standard post hoc filtering using nearest-neighbour stress. Furthermore, we demonstrate empirically that the proposed method offers a promising solution to linkage map construction in the case of a reciprocal translocation.

PERGOLA: fast and deterministic linkage mapping of polyploids

BACKGROUND

A large share of agriculturally and horticulturally important plant species are polyploid. Linkage maps are used to locate associations between genes and traits by breeders and geneticists. Linkage map creation for polyploid species is not supported by standard tools. We want to overcome this limitation and validate our results with simulation studies.

RESULTS

We developed PERGOLA, a deterministic and heuristic method that addresses this problem. We show that it creates correct linkage groups, marker orders and distances for simulated and real datasets. We compare it to existing tools and demonstrate that it overcomes limitations in ploidy and outperforms them in computational time and mapping accuracy. We represent linkage maps as dendrograms and show that this has advantages in the comparison of different maps.

CONCLUSIONS

PERGOLA can be used successfully to calculate linkage maps for diploid and polyploid species and outperforms existing tools.

A rapid marker ordering approach for high-density genetic linkage maps in experimental autotetraploid populations using multidimensional scaling

The paper proposes and validates a robust method for rapid construction of high-density linkage maps suitable for autotetraploid species. Modern genotyping techniques are producing increasingly high numbers of genetic markers that can be scored in experimental populations of plants and animals. Ordering these markers to form a reliable linkage map is computationally challenging. There is a wide literature on this topic, but most has focussed on populations derived from diploid, homozygous parents. The challenge of ordering markers in an autotetraploid population has received little attention, and there is currently no method that runs sufficiently rapidly to investigate the effects of omitting problematic markers on map order in larger datasets. Here, we have explored the use of multidimensional scaling (MDS) to order markers from a cross between autotetraploid parents, using simulated data with 74-152 markers on a linkage group and also experimental data from a potato population. We compared different functions of the recombination fraction and LOD score to form the MDS stress function and found that an LOD² weighting generally performed well, including when missing values and genotyping errors are present. We conclude that an initial analysis using unconstrained MDS gives a rapid method to detect and remove problematic markers, and that a subsequent analysis using either constrained MDS or principal curve analysis gives reliable marker orders. The latter approach is also particularly rapid, taking less than 10 s on a set of 258 markers compared to 6 days for the JoinMap software. This MDS approach could also be applied to experimental populations of diploid species.

A high-density genetic map reveals variation in recombination rate across the genome of Daphnia magna

BACKGROUND

Recombination rate is an essential parameter for many genetic analyses. Recombination rates are highly variable across species, populations, individuals and different genomic regions. Due to the profound influence that recombination can have on intraspecific diversity and interspecific divergence, characterization of recombination rate variation emerges as a key resource for population genomic studies and emphasises the importance of high-density genetic maps as tools for studying genome biology. Here we present such a high-density genetic map for Daphnia magna, and analyse patterns of recombination rate across the genome.

RESULTS

A F2 intercross panel was genotyped by Restriction-site Associated DNA sequencing to construct the third-generation linkage map of D. magna. The resulting high-density map included 4037 markers covering 813 scaffolds and contigs that sum up to 77 % of the currently available genome draft sequence (v2.4) and 55 % of the estimated genome size (238 Mb). Total genetic length of the map presented here is 1614.5 cM and the genome-wide recombination rate is estimated to 6.78 cM/Mb. Merging genetic and physical information we consistently found that recombination rate estimates are high towards the peripheral parts of the chromosomes, while chromosome centres, harbouring centromeres in D. magna, show very low recombination rate estimates.

CONCLUSIONS

Due to its high-density, the third-generation linkage map for D. magna can be coupled with the draft genome assembly, providing an essential tool for genome investigation in this model organism. Thus, our linkage map can be used for the on-going improvements of the genome assembly, but more importantly, it has enabled us to characterize variation in recombination rate across the genome of D. magna for the first time. These new insights can provide a valuable assistance in future studies of the genome evolution, mapping of quantitative traits and population genetic studies.

Genetic Mapping of Millions of SNPs in Safflower (Carthamus tinctorius L.) via Whole-Genome Resequencing

Accurate assembly of complete genomes is facilitated by very high density genetic maps. We performed low-coverage, whole-genome shotgun sequencing on 96 F₆ recombinant inbred lines (RILs) of a cross between safflower (Carthamus tinctorius L.) and its wild progenitor (C. palaestinus Eig). We also produced a draft genome assembly of C. tinctorius covering 866 million bp (∼two-thirds) of the expected 1.35 Gbp genome after sequencing a single, short insert library to ∼21 × depth. Sequence reads from the RILs were mapped to this genome assembly to facilitate SNP identification, and the resulting polymorphisms were used to construct a genetic map. The resulting map included 2,008,196 genetically located SNPs in 1178 unique positions. A total of 57,270 scaffolds, each containing five or more mapped SNPs, were anchored to the map. This resulted in the assignment of sequence covering 14% of the expected genome length to a genetic position. Comparison of this safflower map to genetic maps of sunflower and lettuce revealed numerous chromosomal rearrangements, and the resulting patterns were consistent with a whole-genome duplication event in the lineage leading to sunflower. This sequence-based genetic map provides a powerful tool for the assembly of a low-cost draft genome of safflower, and the same general approach is expected to work for other species.

Exploiting genotyping by sequencing to characterize the genomic structure of the American cranberry through high-density linkage mapping

Background

The application of genotyping by sequencing (GBS) approaches, combined with data imputation methodologies, is narrowing the genetic knowledge gap between major and understudied, minor crops. GBS is an excellent tool to characterize the genomic structure of recently domesticated (~200 years) and understudied species, such as cranberry (Vaccinium macrocarpon Ait.), by generating large numbers of markers for genomic studies such as genetic mapping.

Results

We identified 10842 potentially mappable single nucleotide polymorphisms (SNPs) in a cranberry pseudo-testcross population wherein 5477 SNPs and 211 short sequence repeats (SSRs) were used to construct a high density linkage map in cranberry of which a total of 4849 markers were mapped. Recombination frequency, linkage disequilibrium (LD), and segregation distortion at the genomic level in the parental and integrated linkage maps were characterized for first time in cranberry. SSR markers, used as the backbone in the map, revealed high collinearity with previously published linkage maps. The 4849 point map consisted of twelve linkage groups spanning 1112 cM, which anchored 2381 nuclear scaffolds accounting for ~13 Mb of the estimated 470 Mb cranberry genome. Bin mapping identified 592 and 672 unique bins in the parentals and a total of 1676 unique marker positions in the integrated map. Synteny analyses comparing the order of anchored cranberry scaffolds to their homologous positions in kiwifruit, grape, and coffee genomes provided initial evidence of homology between cranberry and closely related species.

Conclusions

GBS data was used to rapidly saturate the cranberry genome with markers in a pseudo-testcross population. Collinearity between the present saturated genetic map and previous cranberry SSR maps suggests that the SNP locations represent accurate marker order and chromosome structure of the cranberry genome. SNPs greatly improved current marker genome coverage, which allowed for genome-wide structure investigations such as segregation distortion, recombination, linkage disequilibrium, and synteny analyses. In the future, GBS can be used to accelerate cranberry molecular breeding through QTL mapping and genome-wide association studies (GWAS).

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-2802-3) contains supplementary material, which is available to authorized users.

A highly recombined, high-density, eight-founder wheat MAGIC map reveals extensive segregation distortion and genomic locations of introgression segments

Multiparent Advanced Generation Intercross (MAGIC) mapping populations offer unique opportunities and challenges for marker and QTL mapping in crop species. We have constructed the first eight-parent MAGIC genetic map for wheat, comprising 18 601 SNP markers. We validated the accuracy of our map against the wheat genome sequence and found an improvement in accuracy compared to published genetic maps. Our map shows a notable increase in precision resulting from the three generations of intercrossing required to create the population. This is most pronounced in the pericentromeric regions of the chromosomes. Sixteen percent of mapped markers exhibited segregation distortion (SD) with many occurring in long (>20 cM) blocks. Some of the longest and most distorted blocks were collinear with noncentromeric high-marker-density regions of the genome, suggesting they were candidates for introgression fragments introduced into the bread wheat gene pool from other grass species. We investigated two of these linkage blocks in detail and found strong evidence that one on chromosome 4AL, showing SD against the founder Robigus, is an interspecific introgression fragment. The completed map is available from http://www.niab.com/pages/id/326/Resources.

Analytical and Decision Support Tools for Genomics-Assisted Breeding

To successfully implement genomics-assisted breeding (GAB) in crop improvement programs, efficient and effective analytical and decision support tools (ADSTs) are 'must haves' to evaluate and select plants for developing next-generation crops. Here we review the applications and deployment of appropriate ADSTs for GAB, in the context of next-generation sequencing (NGS), an emerging source of massive genomic information. We discuss suitable software tools and pipelines for marker-based approaches (markers/haplotypes), including large-scale genotypic and phenotypic, data management, and molecular breeding approaches. Although phenotyping remains expensive and time consuming, prediction of allelic effects on phenotypes opens new doors to enhance genetic gain across crop cycles, building on reliable phenotyping approaches and good crop information systems, including pedigree information and target haplotypes.

MaGuS: a tool for quality assessment and scaffolding of genome assemblies with Whole Genome Profiling™ Data

Background

Scaffolding is an essential step in the genome assembly process. Current methods based on large fragment paired-end reads or long reads allow an increase in contiguity but often lack consistency in repetitive regions, resulting in fragmented assemblies. Here, we describe a novel tool to link assemblies to a genome map to aid complex genome reconstruction by detecting assembly errors and allowing scaffold ordering and anchoring.

Results

We present MaGuS (map-guided scaffolding), a modular tool that uses a draft genome assembly, a Whole Genome Profiling™ (WGP) map, and high-throughput paired-end sequencing data to estimate the quality and to enhance the contiguity of an assembly. We generated several assemblies of the Arabidopsis genome using different scaffolding programs and applied MaGuS to select the best assembly using quality metrics. Then, we used MaGuS to perform map-guided scaffolding to increase contiguity by creating new scaffold links in low-covered and highly repetitive regions where other commonly used scaffolding methods lack consistency.

Conclusions

MaGuS is a powerful reference-free evaluator of assembly quality and a WGP map-guided scaffolder that is freely available at https://github.com/institut-de-genomique/MaGuS. Its use can be extended to other high-throughput sequencing data (e.g., long-read data) and also to other map data (e.g., genetic maps) to improve the quality and the contiguity of large and complex genome assemblies.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-016-0969-x) contains supplementary material, which is available to authorized users.

Uncovering multiloci-ordering by algebraic property of Laplacian matrix and its Fiedler vector

MOTIVATION

The loci-ordering, based on two-point recombination fractions for a pair of loci, is the most important step in constructing a reliable and fine genetic map.

RESULTS

Using the concept from complex graph theory, here we propose a Laplacian ordering approach which uncovers the loci-ordering of multiloci simultaneously. The algebraic property for a Fiedler vector of a Laplacian matrix, constructed from the recombination fraction of the loci-ordering for 26 loci of barley chromosome IV, 846 loci of Arabidopsis thaliana and 1903 loci of Malus domestica, together with the variable threshold uncovers their loci-orders. It offers an alternative yet robust approach for ordering multiloci.

AVAILABILITY AND IMPLEMENTATION

Source code program with data set is available as supplementary data and also in a software category of the website (http://biophysics.dgist.ac.kr)

CONTACT

crkim@pusan.ac.kr or iksoochang@dgist.ac.kr

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Characterizing uncertainty in high-density maps from multiparental populations

Multiparental populations are of considerable interest in high-density genetic mapping due to their increased levels of polymorphism and recombination relative to biparental populations. However, errors in map construction can have significant impact on QTL discovery in later stages of analysis, and few methods have been developed to quantify the uncertainty attached to the reported order of markers or intermarker distances. Current methods are computationally intensive or limited to assessing uncertainty only for order or distance, but not both simultaneously. We derive the asymptotic joint distribution of maximum composite likelihood estimators for intermarker distances. This approach allows us to construct hypothesis tests and confidence intervals for simultaneously assessing marker-order instability and distance uncertainty. We investigate the effects of marker density, population size, and founder distribution patterns on map confidence in multiparental populations through simulations. Using these data, we provide guidelines on sample sizes necessary to map markers at sub-centimorgan densities with high certainty. We apply these approaches to data from a bread wheat Multiparent Advanced Generation Inter-Cross (MAGIC) population genotyped using the Illumina 9K SNP chip to assess regions of uncertainty and validate them against the recently released pseudomolecule for the wheat chromosome 3B.

High-Density Single Nucleotide Polymorphism Linkage Maps of Lowland Switchgrass using Genotyping-by-Sequencing

Switchgrass (Panicum virgatum L.) is a warm-season perennial grass with promising potential as a bioenergy crop in the United States. However, the lack of genomic resources has slowed the development of plant lines with optimal characteristics for sustainable feedstock production. We generated high-density single nucleotide polymorphism (SNP) linkage maps using a reduced-representation sequencing approach by genotyping 231 F₁ progeny of a cross between two parents of lowland ecotype from the cultivars Kanlow and Alamo. Over 350 million reads were generated and aligned, which enabled identification and ordering of 4611 high-quality SNPs. The total lengths of the resulting framework maps were 1770 cM for the Kanlow parent and 2059 cM for the Alamo parent. These maps show collinearity with maps generated with polymerase chain reaction (PCR)-based simple-sequence repeat (SSR) markers, and new SNP markers were identified in previously unpopulated regions of the genome. Transmission segregation distortion affected all linkage groups (LGs) to differing degrees, and ordering of distorted markers highlighted several regions of unequal inheritance. Framework maps were adversely affected by the addition of distorted markers with varying severity, but distorted maps were of higher marker density and provided additional information for analysis. Alignment of these linkage maps with a draft version of the switchgrass genome assembly demonstrated high levels of collinearity and provides greater confidence in the validity of both resources. This methodology has proven to be a rapid and cost-effective way to generate high-quality linkage maps of an outcrossing species.

Using linkage maps to correct and scaffold de novo genome assemblies: methods, challenges, and computational tools

Modern high-throughput DNA sequencing has made it possible to inexpensively produce genome sequences, but in practice many of these draft genomes are fragmented and incomplete. Genetic linkage maps based on recombination rates between physical markers have been used in biology for over 100 years and a linkage map, when paired with a de novo sequencing project, can resolve mis-assemblies and anchor chromosome-scale sequences. Here, I summarize the methodology behind integrating de novo assemblies and genetic linkage maps, outline the current challenges, review the available software tools, and discuss new mapping technologies.

High-resolution genetic maps of Eucalyptus improve Eucalyptus grandis genome assembly

Genetic maps are key tools in genetic research as they constitute the framework for many applications, such as quantitative trait locus analysis, and support the assembly of genome sequences. The resequencing of the two parents of a cross between Eucalyptus urophylla and Eucalyptus grandis was used to design a single nucleotide polymorphism (SNP) array of 6000 markers evenly distributed along the E. grandis genome. The genotyping of 1025 offspring enabled the construction of two high-resolution genetic maps containing 1832 and 1773 markers with an average marker interval of 0.45 and 0.5 cM for E. grandis and E. urophylla, respectively. The comparison between genetic maps and the reference genome highlighted 85% of collinear regions. A total of 43 noncollinear regions and 13 nonsynthetic regions were detected and corrected in the new genome assembly. This improved version contains 4943 scaffolds totalling 691.3 Mb of which 88.6% were captured by the 11 chromosomes. The mapping data were also used to investigate the effect of population size and number of markers on linkage mapping accuracy. This study provides the most reliable linkage maps for Eucalyptus and version 2.0 of the E. grandis genome.

PAV markers in Sorghum bicolour: genome pattern, affected genes and pathways, and genetic linkage map construction

KEY MESSAGE

5,511 genic small-size PAVs in sorghum were identified and examined, including the pattern and the function enrichment of PAV genes. 325 PAV markers were developed to construct a genetic map. Presence/absence variants (PAVs) correlate closely to the phenotypic variation, by impacting plant genome sizes and the adaption to the environment. To shed more light on their genome-wide patterns, functions and the possibility of using them as molecular markers, we generated next generation genome sequencing data for four sorghum inbred lines and used associated bioinformatic pipelines to identify small-size PAVs (40-10 kb). Five thousand five hundreds and eleven genic PAVs (40-10 kb) were identified and found to affect 3,238 genes. These PAVs were mainly distributed on the sub-telomeric regions, but the highest proportions occurred in the vicinity of the centromeric regions. One of the prominent features of the PAVs is the high occurrence of long terminal repeats retrotransposons and DNA transposons. PAVs caused various alterations to gene structure, primarily including the coding sequence variants, intron variants, transcript ablation, and initiator codon changes. The genes affected by PAVs were significantly enriched in those involved in stress responses and protein modification. We used 325 PAVs polymorphic between two sorghum inbred lines Ji2731 and E-Tian, together with 49 SSR markers, and constructed a genetic map, which consisted of 10 linkage groups corresponding to the 10 chromosomes of sorghum and spanned 1,430.3 cM in length covering 97% of the physical genome. The resources reported here should be useful for genetic study and breeding of sorghum and related species.

A gene-derived SNP-based high resolution linkage map of carrot including the location of QTL conditioning root and leaf anthocyanin pigmentation

BACKGROUND

Purple carrots accumulate large quantities of anthocyanins in their roots and leaves. These flavonoid pigments possess antioxidant activity and are implicated in providing health benefits. Informative, saturated linkage maps associated with well characterized populations segregating for anthocyanin pigmentation have not been developed. To investigate the genetic architecture conditioning anthocyanin pigmentation we scored root color visually, quantified root anthocyanin pigments by high performance liquid chromatography in segregating F2, F3 and F4 generations of a mapping population, mapped quantitative trait loci (QTL) onto a dense gene-derived single nucleotide polymorphism (SNP)-based linkage map, and performed comparative trait mapping with two unrelated populations.

RESULTS

Root pigmentation, scored visually as presence or absence of purple coloration, segregated in a pattern consistent with a two gene model in an F2, and progeny testing of F3-F4 families confirmed the proposed genetic model. Purple petiole pigmentation was conditioned by a single dominant gene that co-segregates with one of the genes conditioning root pigmentation. Root total pigment estimate (RTPE) was scored as the percentage of the root with purple color.All five anthocyanin glycosides previously reported in carrot, as well as RTPE, varied quantitatively in the F2 population. For the purpose of QTL analysis, a high resolution gene-derived SNP-based linkage map of carrot was constructed with 894 markers covering 635.1 cM with a 1.3 cM map resolution. A total of 15 significant QTL for all anthocyanin pigments and for RTPE mapped to six chromosomes. Eight QTL with the largest phenotypic effects mapped to two regions of chromosome 3 with co-localized QTL for several anthocyanin glycosides and for RTPE. A single dominant gene conditioning anthocyanin acylation was identified and mapped.Comparative mapping with two other carrot populations segregating for purple color indicated that carrot anthocyanin pigmentation is controlled by at least three genes, in contrast to monogenic control reported previously.

CONCLUSIONS

This study generated the first high resolution gene-derived SNP-based linkage map in the Apiaceae. Two regions of chromosome 3 with co-localized QTL for all anthocyanin pigments and for RTPE, largely condition anthocyanin accumulation in carrot roots and leaves. Loci controlling root and petiole anthocyanin pigmentation differ across diverse carrot genetic backgrounds.

Genetic mapping of horizontal stripes in Lake Victoria cichlid fishes: benefits and pitfalls of using RAD markers for dense linkage mapping

The genetic dissection of naturally occurring phenotypes sheds light on many fundamental and longstanding questions in speciation and adaptation and is a central research topic in evolutionary biology. Until recently, forward-genetic approaches were virtually impossible to apply to nonmodel organisms, but the development of next-generation sequencing techniques eases this difficulty. Here, we use the ddRAD-seq method to map a colour trait with a known adaptive function in cichlid fishes, well-known textbook examples for rapid rates of speciation and astonishing phenotypic diversification. A suite of phenotypic key innovations is related to speciation and adaptation in cichlids, among which body coloration features prominently. The focal trait of this study, horizontal stripes, evolved in parallel in several cichlid radiations and is associated with piscivorous foraging behaviour. We conducted interspecific crosses between Haplochromis sauvagei and H. nyererei and constructed a linkage map with 867 SNP markers distributed on 22 linkage groups and total size of 1130.63 cM. Lateral stripes are inherited as a Mendelian trait and map to a single genomic interval that harbours a paralog of a gene with known function in stripe patterning. Dorsolateral and mid-lateral stripes were always coinherited and are thus under the same genetic control. Additionally, we directly quantify the genotyping error rates in RAD markers and offer guidelines for identifying and dealing with errors. Uncritical marker selection was found to severely impact linkage map construction. Fortunately, by applying appropriate quality control steps, a genotyping accuracy of >99.9% can be reached, thus allowing for efficient linkage mapping of evolutionarily relevant traits.

Genetic anchoring of whole-genome shotgun assemblies

The recent advances in sequencing throughput and genome assembly algorithms have established whole-genome shotgun (WGS) assemblies as the cornerstone of the genomic infrastructure for many species. WGS assemblies can be constructed with comparative ease and give a comprehensive representation of the gene space even of large and complex genomes. One major obstacle in utilizing WGS assemblies for important research applications such as gene isolation or comparative genomics has been the lack of chromosomal positioning and contextualization of short sequence contigs. Assigning chromosomal locations to sequence contigs required the construction and integration of genome-wide physical maps and dense genetic linkage maps as well as synteny to model species. Recently, methods to rapidly construct ultra-dense linkage maps encompassing millions of genetic markers from WGS sequencing data of segregating populations have made possible the direct assignment of genetic positions to short sequence contigs. Here, we review recent developments in the integration of WGS assemblies and sequence-based linkage maps, discuss challenges for further improvement of the methodology and outline possible applications building on genetically anchored WGS assemblies.

Chromosomal evolution and patterns of introgression in helianthus

Knowledge of the nature and extent of karyotypic differences between species provides insight into the evolutionary history of the genomes in question and, in the case of closely related species, the potential for genetic exchange between taxa. We constructed high-density genetic maps of the silverleaf sunflower (Helianthus argophyllus) and Algodones Dune sunflower (H. niveus ssp. tephrodes) genomes and compared them to a consensus map of cultivated sunflower (H. annuus) to identify chromosomal rearrangements between species. The genetic maps of H. argophyllus and H. niveus ssp. tephrodes included 17 linkage groups each and spanned 1337 and 1478 cM, respectively. Comparative analyses revealed greater divergence between H. annuus and H. niveus ssp. tephrodes (13 inverted segments, 18 translocated segments) than between H. annuus and H. argophyllus (10 inverted segments, 8 translocated segments), consistent with their known phylogenetic relationships. Marker order was conserved across much of the genome, with 83 and 64% of the H. argophyllus and H. niveus ssp. tephrodes genomes, respectively, being syntenic with H. annuus. Population genomic analyses between H. annuus and H. argophyllus, which are sympatric across a portion of the natural range of H. annuus, revealed significantly elevated genetic structure in rearranged portions of the genome, indicating that such rearrangements are associated with restricted gene flow between these two species.

A high-density SNP map for accurate mapping of seed fibre QTL in Brassica napus L

A high density genetic linkage map for the complex allotetraploid crop species Brassica napus (oilseed rape) was constructed in a late-generation recombinant inbred line (RIL) population, using genome-wide single nucleotide polymorphism (SNP) markers assayed by the Brassica 60 K Infinium BeadChip Array. The linkage map contains 9164 SNP markers covering 1832.9 cM. 1232 bins account for 7648 of the markers. A subset of 2795 SNP markers, with an average distance of 0.66 cM between adjacent markers, was applied for QTL mapping of seed colour and the cell wall fiber components acid detergent lignin (ADL), cellulose and hemicellulose. After phenotypic analyses across four different environments a total of 11 QTL were detected for seed colour and fiber traits. The high-density map considerably improved QTL resolution compared to the previous low-density maps. A previously identified major QTL with very high effects on seed colour and ADL was pinpointed to a narrow genome interval on chromosome A09, while a minor QTL explaining 8.1% to 14.1% of variation for ADL was detected on chromosome C05. Five and three QTL accounting for 4.7% to 21.9% and 7.3% to 16.9% of the phenotypic variation for cellulose and hemicellulose, respectively, were also detected. To our knowledge this is the first description of QTL for seed cellulose and hemicellulose in B. napus, representing interesting new targets for improving oil content. The high density SNP genetic map enables navigation from interesting B. napus QTL to Brassica genome sequences, giving useful new information for understanding the genetics of key seed quality traits in rapeseed.

GATA transcription factors in vertebrates: evolutionary, structural and functional interplay

GATA transcription factors perform conserved and essential roles during animal development, including germ-layer specification, hematopoiesis, and cardiogenesis. The evolutionary history and the changes in selection pressures following duplication of the six GATA family members in vertebrates have not been completely understood. Recently, we explored multiple databases to find GATAs in different vertebrate species. Using these sequences, we have performed molecular phylogenetic analyses using Maximum Likelihood and Bayesian methods, and statistical tests of tree topologies, to ascertain the phylogenetic relationship and selection pressures among GATA proteins. Seventy-one full-length cDNA sequences from 24 vertebrate species were extracted from multiple databases. By phylogenetic analyses, we investigated the origin, conservation, and evolution of the GATAs. Six GATA genes in vertebrates might be formed by gene duplication. The inferred evolutionary transitions that separate members which belong to different gene clusters correlated with changes in functional properties. Selection analysis and protein structure analysis were combined to explain Darwinian selection in GATA sequences and these changes brought putative biological significance. 26 positive selection sites were detected in this process. This study reveals the evolutionary history of vertebrate GATA paralogous and positively selected sites likely relevant for the distinct functional properties of the paralogs. It provides a new perspective for understanding the origin and evolution and biological functions of GATAs, which will help to uncover the GATAs' biological roles, evolution and their relationship with associated diseases; in addition, other complex multidomain families and also larger superfamilies can be investigated in a similar way.

High-throughput genomics in sorghum: from whole-genome resequencing to a SNP screening array

With its small, diploid and completely sequenced genome, sorghum (Sorghum bicolor L. Moench) is highly amenable to genomics-based breeding approaches. Here, we describe the development and testing of a robust single-nucleotide polymorphism (SNP) array platform that enables polymorphism screening for genome-wide and trait-linked polymorphisms in genetically diverse S. bicolor populations. Whole-genome sequences with 6× to 12× coverage from five genetically diverse S. bicolor genotypes, including three sweet sorghums and two grain sorghums, were aligned to the sorghum reference genome. From over 1 million high-quality SNPs, we selected 2124 Infinium Type II SNPs that were informative in all six source genomes, gave an optimal Assay Design Tool (ADT) score, had allele frequencies of 50% in the six genotypes and were evenly spaced throughout the S. bicolor genome. Furthermore, by phenotype-based pool sequencing, we selected an additional 876 SNPs with a phenotypic association to early-stage chilling tolerance, a key trait for European sorghum breeding. The 3000 attempted bead types were used to populate half of a dual-species Illumina iSelect SNP array. The array was tested using 564 Sorghum spp. genotypes, including offspring from four unrelated recombinant inbred line (RIL) and F2 populations and a genetic diversity collection. A high call rate of over 80% enabled validation of 2620 robust and polymorphic sorghum SNPs, underlining the efficiency of the array development scheme for whole-genome SNP selection and screening, with diverse applications including genetic mapping, genome-wide association studies and genomic selection.

Lep-MAP: fast and accurate linkage map construction for large SNP datasets

MOTIVATION

Current high-throughput sequencing technologies allow cost-efficient genotyping of millions of single nucleotide polymorphisms (SNPs) for hundreds of samples. However, the tools that are currently available for constructing linkage maps are not well suited for large datasets. Linkage maps of large datasets would be helpful in de novo genome assembly by facilitating comprehensive genome validation and refinement by enabling chimeric scaffold detection, as well as in family-based linkage and association studies, quantitative trait locus mapping, analysis of genome synteny and other complex genomic data analyses.

RESULTS

We describe a novel tool, called Lepidoptera-MAP (Lep-MAP), for constructing accurate linkage maps with ultradense genome-wide SNP data. Lep-MAP is fast and memory efficient and largely automated, requiring minimal user interaction. It uses simultaneously data on multiple outbred families and can increase linkage map accuracy by taking into account achiasmatic meiosis, a special feature of Lepidoptera and some other taxa with no recombination in one sex (no recombination in females in Lepidoptera). We demonstrate that Lep-MAP outperforms other methods on real and simulated data. We construct a genome-wide linkage map of the Glanville fritillary butterfly (Melitaea cinxia) with over 40 000 SNPs. The data were generated with a novel in-house SOLiD restriction site-associated DNA tag sequencing protocol, which is described in the online supplementary material.

AVAILABILITY AND IMPLEMENTATION

Java source code under GNU general public license with the compiled classes and the datasets are available from http://sourceforge.net/users/lep-map.

Quantitative trait loci in hop (Humulus lupulus L.) reveal complex genetic architecture underlying variation in sex, yield and cone chemistry

BACKGROUND

Hop (Humulus lupulus L.) is cultivated for its cones, the secondary metabolites of which contribute bitterness, flavour and aroma to beer. Molecular breeding methods, such as marker assisted selection (MAS), have great potential for improving the efficiency of hop breeding. The success of MAS is reliant on the identification of reliable marker-trait associations. This study used quantitative trait loci (QTL) analysis to identify marker-trait associations for hop, focusing on traits related to expediting plant sex identification, increasing yield capacity and improving bittering, flavour and aroma chemistry.

RESULTS

QTL analysis was performed on two new linkage maps incorporating transferable Diversity Arrays Technology (DArT) markers. Sixty-three QTL were identified, influencing 36 of the 50 traits examined. A putative sex-linked marker was validated in a different pedigree, confirming the potential of this marker as a screening tool in hop breeding programs. An ontogenetically stable QTL was identified for the yield trait dry cone weight; and a QTL was identified for essential oil content, which verified the genetic basis for variation in secondary metabolite accumulation in hop cones. A total of 60 QTL were identified for 33 secondary metabolite traits. Of these, 51 were pleiotropic/linked, affecting a substantial number of secondary metabolites; nine were specific to individual secondary metabolites.

CONCLUSIONS

Pleiotropy and linkage, found for the first time to influence multiple hop secondary metabolites, have important implications for molecular selection methods. The selection of particular secondary metabolite profiles using pleiotropic/linked QTL will be challenging because of the difficulty of selecting for specific traits without adversely changing others. QTL specific to individual secondary metabolites, however, offer unequalled value to selection programs. In addition to their potential for selection, the QTL identified in this study advance our understanding of the genetic control of traits of current economic and breeding significance in hop and demonstrate the complex genetic architecture underlying variation in these traits. The linkage information obtained in this study, based on transferable markers, can be used to facilitate the validation of QTL, crucial to the success of MAS.

Genotype imputation accuracy in a F2 pig population using high density and low density SNP panels

Background

F₂ resource populations have been used extensively to map QTL segregating between pig breeds. A limitation associated with the use of these resource populations for fine mapping of QTL is the reduced number of founding individuals and recombinations of founding haplotypes occurring in the population. These limitations, however, become advantageous when attempting to impute unobserved genotypes using within family segregation information. A trade-off would be to re-type F₂ populations using high density SNP panels for founding individuals and low density panels (tagSNP) in F₂ individuals followed by imputation. Subsequently a combined meta-analysis of several populations would provide adequate power and resolution for QTL mapping, and could be achieved at relatively low cost. Such a strategy allows the wealth of phenotypic information that has previously been obtained on experimental resource populations to be further mined for QTL identification. In this study we used experimental and simulated high density genotypes (HD-60K) from an F₂ cross to estimate imputation accuracy under several genotyping scenarios.

Results

Selection of tagSNP using physical distance or linkage disequilibrium information produced similar imputation accuracies. In particular, tagSNP sets averaging 1 SNP every 2.1 Mb (1,200 SNP genome-wide) yielded imputation accuracies (IA) close to 0.97. If instead of using custom panels, the commercially available 9K chip is used in the F₂, IA reaches 0.99. In order to attain such high imputation accuracy the F₀ and F₁ generations should be genotyped at high density. Alternatively, when only the F₀ is genotyped at HD, while F₁ and F₂ are genotyped with a 9K panel, IA drops to 0.90.

Conclusions

Combining 60K and 9K panels with imputation in F₂ populations is an appealing strategy to re-genotype existing populations at a fraction of the cost.

A consensus map of rapeseed (Brassica napus L.) based on diversity array technology markers: applications in genetic dissection of qualitative and quantitative traits

Background

Dense consensus genetic maps based on high-throughput genotyping platforms are valuable for making genetic gains in Brassica napus through quantitative trait locus identification, efficient predictive molecular breeding, and map-based gene cloning. This report describes the construction of the first B. napus consensus map consisting of a 1,359 anchored array based genotyping platform; Diversity Arrays Technology (DArT), and non-DArT markers from six populations originating from Australia, Canada, China and Europe. We aligned the B. napus DArT sequences with genomic scaffolds from Brassica rapa and Brassica oleracea, and identified DArT loci that showed linkage with qualitative and quantitative loci associated with agronomic traits.

Results

The integrated consensus map covered a total of 1,987.2 cM and represented all 19 chromosomes of the A and C genomes, with an average map density of one marker per 1.46 cM, corresponding to approximately 0.88 Mbp of the haploid genome. Through in silico physical mapping 2,457 out of 3,072 (80%) DArT clones were assigned to the genomic scaffolds of B. rapa (A genome) and B. oleracea (C genome). These were used to orientate the genetic consensus map with the chromosomal sequences. The DArT markers showed linkage with previously identified non-DArT markers associated with qualitative and quantitative trait loci for plant architecture, phenological components, seed and oil quality attributes, boron efficiency, sucrose transport, male sterility, and race-specific resistance to blackleg disease.

Conclusions

The DArT markers provide increased marker density across the B. napus genome. Most of the DArT markers represented on the current array were sequenced and aligned with the B. rapa and B. oleracea genomes, providing insight into the Brassica A and C genomes. This information can be utilised for comparative genomics and genomic evolution studies. In summary, this consensus map can be used to (i) integrate new generation markers such as SNP arrays and next generation sequencing data; (ii) anchor physical maps to facilitate assembly of B. napus genome sequences; and (iii) identify candidate genes underlying natural genetic variation for traits of interest.

Switchgrass genomic diversity, ploidy, and evolution: novel insights from a network-based SNP discovery protocol

Switchgrass (Panicum virgatum L.) is a perennial grass that has been designated as an herbaceous model biofuel crop for the United States of America. To facilitate accelerated breeding programs of switchgrass, we developed both an association panel and linkage populations for genome-wide association study (GWAS) and genomic selection (GS). All of the 840 individuals were then genotyped using genotyping by sequencing (GBS), generating 350 GB of sequence in total. As a highly heterozygous polyploid (tetraploid and octoploid) species lacking a reference genome, switchgrass is highly intractable with earlier methodologies of single nucleotide polymorphism (SNP) discovery. To access the genetic diversity of species like switchgrass, we developed a SNP discovery pipeline based on a network approach called the Universal Network-Enabled Analysis Kit (UNEAK). Complexities that hinder single nucleotide polymorphism discovery, such as repeats, paralogs, and sequencing errors, are easily resolved with UNEAK. Here, 1.2 million putative SNPs were discovered in a diverse collection of primarily upland, northern-adapted switchgrass populations. Further analysis of this data set revealed the fundamentally diploid nature of tetraploid switchgrass. Taking advantage of the high conservation of genome structure between switchgrass and foxtail millet (Setaria italica (L.) P. Beauv.), two parent-specific, synteny-based, ultra high-density linkage maps containing a total of 88,217 SNPs were constructed. Also, our results showed clear patterns of isolation-by-distance and isolation-by-ploidy in natural populations of switchgrass. Phylogenetic analysis supported a general south-to-north migration path of switchgrass. In addition, this analysis suggested that upland tetraploid arose from upland octoploid. All together, this study provides unparalleled insights into the diversity, genomic complexity, population structure, phylogeny, phylogeography, ploidy, and evolutionary dynamics of switchgrass.

Recent advances in sequencing technologies have enabled large-scale surveys of genetic diversity in model species with a wholly or partly sequenced reference genome. However, thousands of key species, which are essential for food, health, energy, and ecology, do not have reference genomes. To accelerate their breeding cycle via marker assisted selection, high-throughput genotyping is required for these valuable species, in spite of the absence of reference genomes. Based on genotyping by sequencing (GBS) technology, we developed a new single nucleotide polymorphism (SNP) discovery protocol, the Universal Network-Enabled Analysis Kit (UNEAK), which can be widely used in any species, regardless of genome complexity or the availability of a reference genome. Here we test this protocol on switchgrass, currently the prime energy crop species in the United States of America. In addition to the discovery of over a million SNPs and construction of high-density linkage maps, we provide novel insights into the genome complexity, ploidy, phylogeny, and evolution of switchgrass. This is only the beginning: we believe UNEAK offers the key to the exploration and exploitation of the genetic diversity of thousands of non-model species.

Three-point appraisal of genetic linkage maps

This paper develops a simple diagnostic for the investigation of uncertainty within genetic linkage maps using a Bayesian procedure. The method requires only the genotyping data and the proposed genetic map, and calculates the posterior probability for the possible orders of any set of three markers, accounting for the presence of genotyping error (mistyping) and for missing genotype data. The method uses a Bayesian approach to give insight into conflicts between the order in the proposed map and the genotype scores. The method can also be used to assess the accuracy of a genetic map at different genomic scales and to assess alternative potential marker orders. Simulation and two case studies were used to illustrate the method. In the first case study, the diagnostic revealed conflicts in map ordering for short inter-marker distances that were resolved at a distance of 8-12 cM, except for a set of markers at the end of the linkage group. In the second case study, the ordering did not resolve as distances increase, which could be attributed to regions of the map where many individuals were untyped.

Genomic characterization of DArT markers based on high-density linkage analysis and physical mapping to the Eucalyptus genome

Diversity Arrays Technology (DArT) provides a robust, high throughput, cost-effective method to query thousands of sequence polymorphisms in a single assay. Despite the extensive use of this genotyping platform for numerous plant species, little is known regarding the sequence attributes and genome-wide distribution of DArT markers. We investigated the genomic properties of the 7,680 DArT marker probes of a Eucalyptus array, by sequencing them, constructing a high density linkage map and carrying out detailed physical mapping analyses to the Eucalyptus grandis reference genome. A consensus linkage map with 2,274 DArT markers anchored to 210 microsatellites and a framework map, with improved support for ordering, displayed extensive collinearity with the genome sequence. Only 1.4 Mbp of the 75 Mbp of still unplaced scaffold sequence was captured by 45 linkage mapped but physically unaligned markers to the 11 main Eucalyptus pseudochromosomes, providing compelling evidence for the quality and completeness of the current Eucalyptus genome assembly. A highly significant correspondence was found between the locations of DArT markers and predicted gene models, while most of the 89 DArT probes unaligned to the genome correspond to sequences likely absent in E. grandis, consistent with the pan-genomic feature of this multi-Eucalyptus species DArT array. These comprehensive linkage-to-physical mapping analyses provide novel data regarding the genomic attributes of DArT markers in plant genomes in general and for Eucalyptus in particular. DArT markers preferentially target the gene space and display a largely homogeneous distribution across the genome, thereby providing superb coverage for mapping and genome-wide applications in breeding and diversity studies. Data reported on these ubiquitous properties of DArT markers will be particularly valuable to researchers working on less-studied crop species who already count on DArT genotyping arrays but for which no reference genome is yet available to allow such detailed characterization.

Genetic linkage mapping in fungi: current state, applications, and future trends

Genetic mapping is a basic tool for eukaryotic genomic research. Linkage maps provide insights into genome organization and can be used for genetic studies of traits of interest. A genetic linkage map is a suitable support for the anchoring of whole genome sequences. It allows the localization of genes of interest or quantitative trait loci (QTL) and map-based cloning. While genetic mapping has been extensively used in plant or animal models, this discipline is more recent in fungi. The present article reviews the current status of genetic linkage map research in fungal species. The process of linkage mapping is detailed, from the development of mapping populations to the construction of the final linkage map, and illustrated based on practical examples. The range of specific applications in fungi is browsed, such as the mapping of virulence genes in pathogenic species or the mapping of agronomically relevant QTL in cultivated edible mushrooms. Future prospects are finally discussed in the context of the most recent advances in molecular techniques and the release of numerous fungal genome sequences.

A reference linkage map for Eucalyptus

Background

Genetic linkage maps are invaluable resources in plant research. They provide a key tool for many genetic applications including: mapping quantitative trait loci (QTL); comparative mapping; identifying unlinked (i.e. independent) DNA markers for fingerprinting, population genetics and phylogenetics; assisting genome sequence assembly; relating physical and recombination distances along the genome and map-based cloning of genes. Eucalypts are the dominant tree species in most Australian ecosystems and of economic importance globally as plantation trees. The genome sequence of E. grandis has recently been released providing unprecedented opportunities for genetic and genomic research in the genus. A robust reference linkage map containing sequence-based molecular markers is needed to capitalise on this resource. Several high density linkage maps have recently been constructed for the main commercial forestry species in the genus (E. grandis, E. urophylla and E. globulus) using sequenced Diversity Arrays Technology (DArT) and microsatellite markers. To provide a single reference linkage map for eucalypts a composite map was produced through the integration of data from seven independent mapping experiments (1950 individuals) using a marker-merging method.

Results

The composite map totalled 1107 cM and contained 4101 markers; comprising 3880 DArT, 213 microsatellite and eight candidate genes. Eighty-one DArT markers were mapped to two or more linkage groups, resulting in the 4101 markers being mapped to 4191 map positions. Approximately 13% of DArT markers mapped to identical map positions, thus the composite map contained 3634 unique loci at an average interval of 0.31 cM.

Conclusion

The composite map represents the most saturated linkage map yet produced in Eucalyptus. As the majority of DArT markers contained on the map have been sequenced, the map provides a direct link to the E. grandis genome sequence and will serve as an important reference for progressing eucalypt research.

Characterization of a major QTL for adult plant resistance to stripe rust in US soft red winter wheat

Stripe rust, caused by Puccinia striiformis f. sp. tritici, is an important disease of soft red winter wheat in the eastern region of the USA. Pioneer 26R61 has provided effective resistance to stripe rust for 10 years. To elucidate the genetic basis of the resistance, a mapping population of 178 recombinant inbred lines (RILs) was developed using single-seed descent from a cross between Pioneer 26R61 and the susceptible cultivar AGS 2000. A genetic map with 895 markers covering all 21 chromosomes was used for QTL analysis. One major QTL was detected, explaining up to 56.0% of the mean phenotypic variation, flanked by markers Xbarc124 and Xgwm359, and assigned to the distal 22% of the short arm of wheat chromosome 2A. Evidence showed that it was different from Yr17 derived from Ae. ventricosa, the only formally named Yr gene in 2AS, and the QTL was temporarily designated as YrR61. In addition, a minor QTL, QYr.uga-6AS, probably conditioned high-temperature adult plant resistance. The QTL explained 6-7% of the trait variation. Preliminary test of the flanking markers for YrR61, in two cultivars and two promising breeding lines with Pioneer 26R61 in their pedigree, indicated that YrR61 was present in these cultivars and lines, and these markers could therefore be used in marker-assisted selection.

A Comparative BAC map for the gilthead sea bream (Sparus aurata L.)

This study presents the first comparative BAC map of the gilthead sea bream (Sparus aurata), a highly valuated marine aquaculture fish species in the Mediterranean. High-throughput end sequencing of a BAC library yielded 92,468 reads (60.6 Mbp). Comparative mapping was achieved by anchoring BAC end sequences to the three-spined stickleback (Gasterosteus aculeatus) genome. BACs that were consistently ordered along the stickleback chromosomes accounted for 14,265 clones. A fraction of 5,249 BACs constituted a minimal tiling path that covers 73.5% of the stickleback chromosomes and 70.2% of the genes that have been annotated. The N50 size of 1,485 “BACtigs” consisting of redundant BACs is 337,253 bp. The largest BACtig covers 2.15 Mbp in the stickleback genome. According to the insert size distribution of mapped BACs the sea bream genome is 1.71-fold larger than the stickleback genome. These results represent a valuable tool to researchers in the field and may support future projects to elucidate the whole sea bream genome.