Efficiency of the use of pedigree and molecular marker information in conservation programs

The value of molecular markers and pedigree records, separately or in combination, to assist in the management of conserved populations has been tested. The general strategy for managing the population was to optimize contributions of parents to the next generation for minimizing the global weighted coancestry. Strategies differed in the type of information used to compute global coancestries, the number and type of evaluated individuals, and the system of mating. Genealogical information proved to be very useful (at least for 10 generations of management) to arrange individuals' contributions via the minimization of global coancestry. In fact, the level of expected heterozygosity after 10 generations yielded by this strategy was 88-100% of the maximum possible improvement obtained if the genotype for all loci was known. Marker information was of very limited value if used alone. The amount and degree of polymorphism of markers to be used to compute molecular coancestry had to be high to mimic the performance of the strategy relying on pedigree, especially in the short term (for example, >10 markers per chromosome with 10 alleles each were needed if only the parents' genotype was available). When both sources of information are combined to calculate the coancestry conditional on markers, clear increases in effective population size (Ne) were found, but observed diversity levels (either gene or allelic diversity) in the early generations were quite similar to the ones obtained with pedigree alone. The advantage of including molecular information is greater when information is available on a greater number of individuals (offspring and parents vs. parents only). However, for realistic situations (i.e., large genomes) the benefits of using information on offspring are small. The same conclusions were reached when comparing the use of the different types of information (genealogical or/and molecular) to perform minimum coancestry matings.     

Quantitative genetic variance associated with chromosomal markers in segregating populations

Summary Use of chromosomal markers can accelerate genetic progress for quantitative traits in pedigree selection programs by providing early information on Mendelian segregation effects for individual progeny. Potential effectiveness of selection using markers is determined by the amount of additive genetic variance traced from parents to progeny by the markers. Theoretical equations for the amount of additive genetic variance associated with a marker were derived at the individual level and for a segregating population in joint linkage equilibrium. Factors considered were the number of quantitative trait loci linked to the marker, their individual effects, and recombination rates with the marker. Subsequently, the expected amount of genetic variance associated with a marker in a segregating population was derived. In pedigree selection programs in segregating populations, a considerable fraction of the genetic variance on a chromosome is expected to be associated with a marker located on that chromosome. For an average chromosome in the bovine, this fraction is approximately 40% of the Mendelian segregation variance contributed by the chromosome. The effects of interference and position of the marker on this expectation are relative small. Length of the chromosome has a large effect on the expected variance. Effectiveness of MAS is, however, greatly reduced by lack of polymorphism at the marker and inaccuracy of estimation of chromosome substitution effects. The size of the expected amount of genetic variance associated with a chromosomal marker indicates that, even when the marker is not the active locus, large chromosome substitution effects are not uncommon in segregating populations.     

Marker-assisted selection to increase effective population size by reducing Mendelian segregation variance

Using both the genetic drift and inbreeding approaches, we derive more general equations for effective size (N(e)) of a diploid species under random mating. These equations show explicitly that inbreeding or genetic drift comes from two sources, the variation in the number of offspring from each parent and the variation in contribution between these parents' own paternally and maternally derived genes to their offspring. The first source can be easily and effectively controlled by choosing an equal number of offspring from each family, while the second can be manipulated by using information on genetic markers to reduce the variance due to Mendelian segregation. Marker-assisted selection (MAS) methods to increase N(e) for the whole genome with single or multiple marker loci per chromosome, different numbers of males, and females are developed and implemented in stochastic simulations. The analytical and simulation results show that, although in principle N(e) can be increased indefinitely, the efficiency of MAS is restricted in practice by the amount of marker information, the genome size, and the number of marker-genotyped offspring per family. The assumptions made in developing the theory and methods and the applications of MAS in conservation are discussed.     

From Genotype �� Environment Interaction to Gene �� Environment Interaction

Historically in plant breeding a large number of statistical models has been developed and used for studying genotype × environment interaction. These models have helped plant breeders to assess the stability of economically important traits and to predict the performance of newly developed genotypes evaluated under varying environmental conditions. In the last decade, the use of relatively low numbers of markers has facilitated the mapping of chromosome regions associated with phenotypic variability (e.g., QTL mapping) and, to a lesser extent, revealed the differetial response of these chromosome regions across environments (i.e., QTL × environment interaction). QTL technology has been useful for marker-assisted selection of simple traits; however, it has not been efficient for predicting complex traits affected by a large number of loci. Recently the appearance of cheap, abundant markers has made it possible to saturate the genome with high density markers and use marker information to predict genomic breeding values, thus increasing the precision of genetic value prediction over that achieved with the traditional use of pedigree information. Genomic data also allow assessing chromosome regions through marker effects and studying the pattern of covariablity of marker effects across differential environmental conditions. In this review, we outline the most important models for assessing genotype × environment interaction, QTL × environment interaction, and marker effect (gene) × environment interaction. Since analyzing genetic and genomic data is one of the most challenging statistical problems researchers currently face, different models from different areas of statistical research must be attempted in order to make significant progress in understanding genetic effects and their interaction with environment.     

Reconstruction of the synthetic W7984 x Opata M85 wheat reference population

Reference populations are valuable resources in genetics studies for determining marker order, marker selection, trait mapping, construction of large-insert libraries, cross-referencing marker platforms, and genome sequencing. Reference populations can be propagated indefinitely, they are polymorphic and have normal segregation. Described are two new reference populations who share the same parents of the original wheat reference population Synthetic W7984 (Altar84/ Aegilops tauschii (219) CIGM86.940) x Opata M85, an F(1)-derived doubled haploid population (SynOpDH) of 215 inbred lines and a recombinant inbred population (SynOpRIL) of 2039 F(6) lines derived by single-plant self-pollinations. A linkage map was constructed for the SynOpDH population using 1446 markers. In addition, a core set of 42 SSR markers was genotyped on SynOpRIL. A new approach to identifying a core set of markers used a step-wise selection protocol based on polymorphism, uniform chromosome distribution, and reliability to create nested sets starting with one marker per chromosome, followed by two, four, and six. It is suggested that researchers use these markers as anchors for all future mapping projects to facilitate cross-referencing markers and chromosome locations. To enhance this public resource, researchers are strongly urged to validate line identities and deposit their data in GrainGenes so that others can benefit from the accumulated information.     

Selection strategies for marker-assisted backcrossing with high-throughput marker systems

Application of marker-assisted backcrossing for gene introgression is still limited by the high costs of marker analysis. High-throughput (HT) assays promise to reduce these costs, but new selection strategies are required for their efficient implementation in breeding programs. The objectives of our study were to investigate the properties of HT marker systems compared to single-marker (SM) assays, and to develop optimal selection strategies for marker-assisted backcrossing with HT assays. We employed computer simulations with a genetic model consisting of 10 chromosomes of 160 cM length to investigate the introgression of a dominant target gene. We found that a major advantage of HT marker systems is that they can provide linkage maps with equally spaced markers, whereas the possibility to provide linkage maps with high marker densities smaller than 10 cM is only of secondary use in marker-assisted backcrossing. A three-stage selection strategy that combines selection for recombinants at markers flanking the target gene with SM assays and genome-wide background selection with HT markers in the first backcross generation was more efficient than genome-wide background selection with HT markers alone. Selection strategies that combine SM and HT assays were more efficient than genome-wide background selection with HT assays alone. This result was obtained for a broad range of cost ratios of HT and SM assays. A further considerable reduction of the costs could be achieved if the population size in the first backcross generation was twice the population size in generations BC₂ and BC₃ of a three-generation backcrossing program. We conclude that selection strategies combining SM and HT assays have the potential to greatly increase the efficiency and flexibility of marker-assisted backcrossing.     

A High-Density SNP Map of Sunflower Derived from RAD-Sequencing Facilitating Fine-Mapping of the Rust Resistance Gene R12

A high-resolution genetic map of sunflower was constructed by integrating SNP data from three F₂ mapping populations (HA 89/RHA 464, B-line/RHA 464, and CR 29/RHA 468). The consensus map spanned a total length of 1443.84 cM, and consisted of 5,019 SNP markers derived from RAD tag sequencing and 118 publicly available SSR markers distributed in 17 linkage groups, corresponding to the haploid chromosome number of sunflower. The maximum interval between markers in the consensus map is 12.37 cM and the average distance is 0.28 cM between adjacent markers. Despite a few short-distance inversions in marker order, the consensus map showed high levels of collinearity among individual maps with an average Spearman''s rank correlation coefficient of 0.972 across the genome. The order of the SSR markers on the consensus map was also in agreement with the order of the individual map and with previously published sunflower maps. Three individual and one consensus maps revealed the uneven distribution of markers across the genome. Additionally, we performed fine mapping and marker validation of the rust resistance gene R₁₂, providing closely linked SNP markers for marker-assisted selection of this gene in sunflower breeding programs. This high resolution consensus map will serve as a valuable tool to the sunflower community for studying marker-trait association of important agronomic traits, marker assisted breeding, map-based gene cloning, and comparative mapping.     

Predictors of marker-informativeness for an outbred F2 design

Generalization of the polymorphism information content (PIC) index to represent marker informativeness (MI) for a three-generation F2 design requires that two additional sources of non-informativeness be added to the PIC formula: the probability of matings between like-heterozygous F1 individuals, of which one is non-informative; and that of matings between like-heterozygous F1 individuals, which are both fully informative but where line of origin of the same alleles is reciprocal. Given the dense marker-maps currently available for some species, this F2 informativeness parameter constitutes the natural criterion for marker selection in F2 designs, and two computer programs to predict MI from grandparental marker-genotypes were developed for an F2 population originating from two divergent selection lines of outbred mice (F approximately 0.2). A total of 403 markers had been genotyped for the F0 grandparents (n=31), and 14 markers had also been genotyped in the complete pedigree including 559 F2 individuals. One program was based on assumptions of random-mating (RM), while the other (PED) accounted for the pedigreed mating structure. For the 403 markers, the correlation between MI from RM and from PED was 0.95, and the average deviation between the two predictions was 0.005 MI units (MI ranged from 0 to 1). Correlations between predicted and realized MI for the 14 fully genotyped markers were 0.97 for PED and 0.94 for RM, while the corresponding average of deviations between predicted and actual values were 0.01 and 0.04, respectively. Absolute deviations from realized MI never exceeded 0.09 and 0.16 for PED and RM, respectively. Simulated optimization of the mating system to maximize average MI of 28 markers on one chromosome led to improvements in the range of 15-20% average MI (0.07-0.09 MI units). The degree of relative advantage conferred by the F2 generalization of the PIC index over the traditional index was found to be of minor significance.     

Aroma in rice: genetic analysis of a quantitative trait

A new approach was developed which succeeded in tagging for the first time a major gene and two QTLs controlling grain aroma in rice. It involved a combination of two techniques, quantification of volatile compounds in the cooking water by gas chromatography, and molecular marker mapping. Four types of molecular marker were used (RFLPs, RAPDs, STSs, isozymes). Evaluation and mapping were performed on a doubled haploid line population which (1) conferred a precise character evaluation by enabling the analysis of large quantities of grains per genotype and (2) made possible the comparison of gas chromatography results and sensitive tests. The population size (135 lines) provided a good mapping precision. Several markers on chromosome 8 were found to be closely linked to a major gene controlling the presence of 2-acetyl-1-pyrroline (AcPy), the main compound of rice aroma. Moreover, our results showed that AcPy concentration in plants is regulated by at least two chromosomal regions. Estimations of recombination fractions on chromosome 8 were corrected for strong segregation distortion. This study confirms that AcPy is the major component of aroma. Use of the markers linked to AcPy major gene and QTLs for marker-assisted selection by successive backcrosses may be envisaged.     

Application of whole genome re-sequencing data in the development of diagnostic DNA markers tightly linked to a disease-resistance locus for marker-assisted selection in lupin (Lupinus angustifolius)

Background

Molecular marker-assisted breeding provides an efficient tool to develop improved crop varieties. A major challenge for the broad application of markers in marker-assisted selection is that the marker phenotypes must match plant phenotypes in a wide range of breeding germplasm. In this study, we used the legume crop species Lupinus angustifolius (lupin) to demonstrate the utility of whole genome sequencing and re-sequencing on the development of diagnostic markers for molecular plant breeding.

Results

Nine lupin cultivars released in Australia from 1973 to 2007 were subjected to whole genome re-sequencing. The re-sequencing data together with the reference genome sequence data were used in marker development, which revealed 180,596 to 795,735 SNP markers from pairwise comparisons among the cultivars. A total of 207,887 markers were anchored on the lupin genetic linkage map. Marker mining obtained an average of 387 SNP markers and 87 InDel markers for each of the 24 genome sequence assembly scaffolds bearing markers linked to 11 genes of agronomic interest. Using the R gene PhtjR conferring resistance to phomopsis stem blight disease as a test case, we discovered 17 candidate diagnostic markers by genotyping and selecting markers on a genetic linkage map. A further 243 candidate diagnostic markers were discovered by marker mining on a scaffold bearing non-diagnostic markers linked to the PhtjR gene. Nine out from the ten tested candidate diagnostic markers were confirmed as truly diagnostic on a broad range of commercial cultivars. Markers developed using these strategies meet the requirements for broad application in molecular plant breeding.

Conclusions

We demonstrated that low-cost genome sequencing and re-sequencing data were sufficient and very effective in the development of diagnostic markers for marker-assisted selection. The strategies used in this study may be applied to any trait or plant species. Whole genome sequencing and re-sequencing provides a powerful tool to overcome current limitations in molecular plant breeding, which will enable plant breeders to precisely pyramid favourable genes to develop super crop varieties to meet future food demands.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1878-5) contains supplementary material, which is available to authorized users.     

Prediction of identity by descent probabilities from marker-haplotypes

The prediction of identity by descent (IBD) probabilities is essential for all methods that map quantitative trait loci (QTL). The IBD probabilities may be predicted from marker genotypes and/or pedigree information. Here, a method is presented that predicts IBD probabilities at a given chromosomal location given data on a haplotype of markers spanning that position. The method is based on a simplification of the coalescence process, and assumes that the number of generations since the base population and effective population size is known, although effective size may be estimated from the data. The probability that two gametes are IBD at a particular locus increases as the number of markers surrounding the locus with identical alleles increases. This effect is more pronounced when effective population size is high. Hence as effective population size increases, the IBD probabilities become more sensitive to the marker data which should favour finer scale mapping of the QTL. The IBD probability prediction method was developed for the situation where the pedigree of the animals was unknown (i.e. all information came from the marker genotypes), and the situation where, say T, generations of unknown pedigree are followed by some generations where pedigree and marker genotypes are known.     

Using Markers in Gene Introgression Breeding Programs

We investigate the use of markers to hasten the recovery of the recipient genome during an introgression breeding program. The effects of time and intensity of selection, population size, number and position of selected markers are studied for chromosomes either carrying or not carrying the introgressed gene. We show that marker assisted selection may lead to a gain in time of about two generations, an efficiency below previous theoretical predictions. Markers are most useful when their map position is known. In the early generations, it is shown that increasing the number of markers over three per non-carrier chromosome is not efficient, that the segment surrounding the introgressed gene is better controlled by rather distant markers unless high selection intensity can be applied, and that selection on this segment first can reduce the selection intensity available for selection on non-carrier chromosomes. These results are used to propose an optimal strategy for selection on the whole genome, making the most of available material and conditions (e.g., population size and fertility, genetic map).     

High-density genetic map of durum wheat × wild emmer wheat based on SSR and DArT markers

A genetic linkage map of tetraploid wheat was constructed based on a cross between durum wheat [Triticum turgidum ssp. durum (Desf.) MacKey] cultivar Langdon and wild emmer wheat [T. turgidum ssp. dicoccoides (K?rn.) Thell.] accession G18-16. One hundred and fifty-two single-seed descent derived F(6) recombinant inbred lines (RILs) were analyzed with a total of 690 loci, including 197 microsatellite and 493 DArT markers. Linkage analysis defined 14 linkage groups. Most markers were mapped to the B-genome (60%), with an average of 57 markers per chromosome and the remaining 40% mapped to the A-genome, with an average of 39 markers per chromosome. To construct a stabilized (skeleton) map, markers interfering with map stability were removed. The skeleton map consisted of 307 markers with a total length of 2,317 cM and average distance of 7.5 cM between adjacent markers. The length of individual chromosomes ranged between 112 cM for chromosome 4B to 217 cM for chromosome 3B. A fraction (30.1%) of the markers deviated significantly from the expected Mendelian ratios; clusters of loci showing distorted segregation were found on chromosomes 1A, 1BL, 2BS, 3B, and 4B. DArT markers showed high proportion of clustering, which may be indicative of gene-rich regions. Three hundred and fifty-two new DArT markers were mapped for the first time on the current map. This map provides a useful groundwork for further genetic analyses of important quantitative traits, positional cloning, and marker-assisted selection, as well as for genome comparative genomics and genome organization studies in wheat and other cereals.     

High-density genetic map of <Emphasis Type="Italic">Populus deltoides</Emphasis> constructed by using specific length amplified fragment sequencing

Populus deltoides is an important industrial tree species widely planted in many areas of the world, and de novo genome sequencing of this plant has been carried out by several research groups. A dense genetic map associating genome sequences is highly desirable for reconstructing the chromosome pseudomolecules using the obtained sequence scaffold assemblies. For this purpose, an intraspecific full-sib F₁ mapping pedigree was established by using the sequenced P. deltoides as the maternal parent. With this mapping pedigree, we constructed a high-density genetic map using 92 randomly selected progenies. Single nucleotide polymorphism (SNP) markers were discovered by using specific length amplified fragment sequencing (SLAF-seq). In total, 487,038 SLAFs were generated, of which 179,360 were polymorphic. A high-density genetic map was built using HighMap software, which included 11,680 Mendelian segregation markers distributing in 2851 marker bins. The established map consisted of 19 linkage groups (LGs) that equaled to the 19 haploid chromosomes in poplar genome, and spanned a total genetic length of 3494.66 cM, with an average distance of 1.23 cM per marker bin. The map presented here will be useful for anchoring the genome sequence assemblies along chromosomes, and for many other aspects of genetic studies on P. deltoides and the closely related species.     

Genome Wide Characterization of Short Tandem Repeat Markers in Sweet Orange (Citrus sinensis)

Sweet orange (Citrus sinensis) is one of the major cultivated and most-consumed citrus species. With the goal of enhancing the genomic resources in citrus, we surveyed, developed and characterized microsatellite markers in the ≈347 Mb sequence assembly of the sweet orange genome. A total of 50,846 SSRs were identified with a frequency of 146.4 SSRs/Mbp. Dinucleotide repeats are the most frequent repeat class and the highest density of SSRs was found in chromosome 4. SSRs are non-randomly distributed in the genome and most of the SSRs (62.02%) are located in the intergenic regions. We found that AT-rich SSRs are more frequent than GC-rich SSRs. A total number of 21,248 SSR primers were successfully developed, which represents 89 SSR markers per Mb of the genome. A subset of 950 developed SSR primer pairs were synthesized and tested by wet lab experiments on a set of 16 citrus accessions. In total we identified 534 (56.21%) polymorphic SSR markers that will be useful in citrus improvement. The number of amplified alleles ranges from 2 to 12 with an average of 4 alleles per marker and an average PIC value of 0.75. The newly developed sweet orange primer sequences, their in silico PCR products, exact position in the genome assembly and putative function are made publicly available. We present the largest number of SSR markers ever developed for a citrus species. Almost two thirds of the markers are transferable to 16 citrus relatives and may be used for constructing a high density linkage map. In addition, they are valuable for marker-assisted selection studies, population structure analyses and comparative genomic studies of C. sinensis with other citrus related species. Altogether, these markers provide a significant contribution to the citrus research community.     

Pedigree and marker information requirements to monitor genetic variability

There are several measures available to describe the genetic variability of populations. The average inbreeding coefficient of a population based on pedigree information is a frequently chosen option. Due to the developments in molecular genetics it is also possible to calculate inbreeding coefficients based on genetic marker information. A simulation study was carried out involving ten sires and 50 dams. The animals were mated over a period of 20 discrete generations. The population size was kept constant. Different situations with regard to the level of polymorphism and initial allele frequencies and mating scheme (random mating, avoidance of full sib mating, avoidance of full sib and half sib mating) were considered. Pedigree inbreeding coefficients of the last generation using full pedigree or 10, 5 and 2 generations of the pedigree were calculated. Marker inbreeding coefficients based on different sets of microsatellite loci were also investigated. Under random mating, pedigree-inbreeding coefficients are clearly more closely related to true autozygosity (i.e., the actual proportion of loci with alleles identical by descent) than marker-inbreeding coefficients. If mating is not random, the demands on the quality and quantity of pedigree records increase. Greater attention must be paid to the correct parentage of the animals.     

Selection strategies for the development of rye introgression libraries

Computer simulations can be employed to find optimal procedures for developing introgression libraries in rye with marker-assisted backcrossing. Our objectives were to investigate the effects of the employed (1) breeding scheme, (2) selection strategy, and (3) population sizes on the donor genome coverage of the library, the number of introgression lines carrying additional donor chromosome segments outside the target regions, and the number of required marker data points. With respect to these target criteria, a BC₃S₂ breeding scheme and increasing population sizes from early to advanced generations were superior to a BC₂S₃ breeding scheme and constant population sizes. The smallest number of donor segments outside the target regions was reached with a three-stage selection strategy, which consists on selection for the target segment, selection for recombination at flanking markers and selection for recurrent parent alleles across the entire genome. Omitting the selection for flanking markers in generation BC₁ reduced considerably the number of required marker data points. A pre-selection of chromosomes consisting completely of donor genome in BC₁ was advantageous, if the effort in the breeding nursery should kept minimum. Adopting the described designs can help rye breeders to successfully develop introgression libraries.     

How many polymorphic marker genes will it take to span the human genome?

It is desirable to know how many polymorphic marker loci will be required so that every human genetic locus can be mapped by classical pedigree methods to a specific region of a specific chromosome. Assuming a total autosomal map length of 33 morgans, it would take only about 33/(2d) evenly spaced markers for every locus to be within d morgans of a marker. Taking into account that the markers will fall randomly along the genome, we show that a much larger number of such loci will have to be isolated and tested before the goal of a saturated gene map is reached.     

Parametric and nonparametric linkage analysis: a unified multipoint approach.

In complex disease studies, it is crucial to perform multipoint linkage analysis with many markers and to use robust nonparametric methods that take account of all pedigree information. Currently available methods fall short in both regards. In this paper, we describe how to extract complete multipoint inheritance information from general pedigrees of moderate size. This information is captured in the multipoint inheritance distribution, which provides a framework for a unified approach to both parametric and nonparametric methods of linkage analysis. Specifically, the approach includes the following: (1) Rapid exact computation of multipoint LOD scores involving dozens of highly polymorphic markers, even in the presence of loops and missing data. (2) Non-parametric linkage (NPL) analysis, a powerful new approach to pedigree analysis. We show that NPL is robust to uncertainty about mode of inheritance, is much more powerful than commonly used nonparametric methods, and loses little power relative to parametric linkage analysis. NPL thus appears to be the method of choice for pedigree studies of complex traits. (3) Information-content mapping, which measures the fraction of the total inheritance information extracted by the available marker data and points out the regions in which typing additional markers is most useful. (4) Maximum-likelihood reconstruction of many-marker haplotypes, even in pedigrees with missing data. We have implemented NPL analysis, LOD-score computation, information-content mapping, and haplotype reconstruction in a new computer package, GENEHUNTER. The package allows efficient multipoint analysis of pedigree data to be performed rapidly in a single user-friendly environment.     

Genetic mapping of the loquat canker resistance locus in bronze loquat (Eriobotrya deflexa)

Loquat canker disease, caused by Pseudomonas syringae pv. eriobotryae, is one of the most harmful diseases of commercial cultivars of loquat (Eriobotrya japonica). To introgress resistance to loquat canker, we identified the linkage group and position of the resistance locus derived from the related wild species bronze loquat (Eriobotrya deflexa). The segregation of resistance and susceptibility fit the expected ratio of 1:1 in 96 individuals from a three-way cross involving bronze loquat (heterozygous for resistance) and two cultivars of loquat (susceptible). The genomic region containing Pse-a was identified by using a genome scanning approach, and the loquat canker resistance locus was mapped at the top of linkage group 10 by applying novel simple sequence repeat (SSR) markers designed on the basis of the ‘Golden Delicious’ apple genome sequence. The constructed linkage group spans 69.4 cM and has an average marker density of 2.6 cM per marker. The developed molecular markers tightly linked to the loquat canker resistance locus will be useful for marker-assisted selection and for introgression of resistance into loquat in breeding programs.