Bulk segregant analysis with molecular markers and its use for improving drought resistance in maize

The usual method to locate and compare loci regulating quantitative traits (QTLs) requires a segregating population of plants with each one genotyped with molecular markers. However, plants from such segregating populations can also be grouped according to phenotypic expression of a trait and tested for differences in allele frequency between the population bulks: bulk segregant analysis (BSA). The same probes used for making a genetic map (e.g. isozyme, RFLP, RAPD, etc) can be used for BSA. A molecular marker showing polymorphism between the parents of the population and which is closely-linked to a major QTL regulating a particular trait will mainly co-segregate with that QTL, i.e. segregate according to the phenotype if the QTL has a large effect. Thus, if plants are grouped according to expression of the trait and extreme groups tested with that polymorphic marker, the frequency of the two marker alleles present within each of the two bulks should deviate significantly from the ratio of 1 : 1 expected for most populations. As chromosomal locations of many molecular markers have now been determined in many species, the map location of closely-linked QTLs can therefore be deduced without having to genotype every individual in segregating populations. This has been used successfully with composite populations of maize to locate QTLs associated with yield under severe drought. An inbred line derived from one of the populations selected for higher drought yield has been crossed with a drought-susceptible inbred line to produce a mapping population for QTL analysis of physiological and developmental traits likely to regulate yield under drought. Future work to identify traits having QTLs with flanking markers showing significant allele frequency differences in the GSA studies will indicate those traits likely to be important in determining yield under drought.Key words: Bulk segregant analysis (BSA), drought resistance, genetic maps, maize, molecular markers, Zea mays (L.).      

Detection of base substitution-type somatic mosaicism of the NLRP3 gene with >99.9% statistical confidence by massively parallel sequencing

Chronic infantile neurological cutaneous and articular syndrome (CINCA), also known as neonatal-onset multisystem inflammatory disease (NOMID), is a dominantly inherited systemic autoinflammatory disease and is caused by a heterozygous germline gain-of-function mutation in the NLRP3 gene. We recently found a high incidence of NLRP3 somatic mosaicism in apparently mutation-negative CINCA/NOMID patients using subcloning and subsequent capillary DNA sequencing. It is important to rapidly diagnose somatic NLRP3 mosaicism to ensure proper treatment. However, this approach requires large investments of time, cost, and labour that prevent routine genetic diagnosis of low-level somatic NLRP3 mosaicism. We developed a routine pipeline to detect even a low-level allele of NLRP3 with statistical significance using massively parallel DNA sequencing. To address the critical concern of discriminating a low-level allele from sequencing errors, we first constructed error rate maps of 14 polymerase chain reaction products covering the entire coding NLRP3 exons on a Roche 454 GS-FLX sequencer from 50 control samples without mosaicism. Based on these results, we formulated a statistical confidence value for each sequence variation in each strand to discriminate sequencing errors from real genetic variation even in a low-level allele, and thereby detected base substitutions at an allele frequency as low as 1% with 99.9% or higher confidence.     

Mapping of Quantitative Trait Loci Underlying Cold Tolerance in Rice Seedlings via High-Throughput Sequencing of Pooled Extremes

Low temperature is a major limiting factor in rice growth and development. Mapping of quantitative trait loci (QTLs) controlling cold tolerance is important for rice breeding. Recent studies have suggested that bulked segregant analysis (BSA) combined with next-generation sequencing (NGS) can be an efficient and cost-effective way for QTL mapping. In this study, we employed NGS-assisted BSA to map QTLs conferring cold tolerance at the seedling stage in rice. By deep sequencing of a pair of large DNA pools acquired from a very large F₃ population (10,800 individuals), we obtained ∼450,000 single nucleotide polymorphisms (SNPs) after strict screening. We employed two statistical methods for QTL analysis based on these SNPs, which yielded consistent results. Six QTLs were mapped on chromosomes 1, 2, 5, 8 and 10. The three most significant QTLs on chromosomes 1, 2 and 8 were validated by comparison with previous studies. Two QTLs on chromosomes 2 and 5 were also identified previously, but at the booting stage rather than the seedling stage, suggesting that some QTLs may function at different developmental stages, which would be useful for cold tolerance breeding in rice. Compared with previously reported QTL mapping studies for cold tolerance in rice based on the traditional approaches, the results of this study demonstrated the advantages of NGS-assisted BSA in both efficiency and statistical power.     

QTL sequencing strategy to map genomic regions associated with resistance to ascochyta blight in chickpea

Whole‐genome sequencing‐based bulked segregant analysis (BSA) for mapping quantitative trait loci (QTL) provides an efficient alternative approach to conventional QTL analysis as it significantly reduces the scale and cost of analysis with comparable power to QTL detection using full mapping population. We tested the application of next‐generation sequencing (NGS)‐based BSA approach for mapping QTLs for ascochyta blight resistance in chickpea using two recombinant inbred line populations CPR‐01 and CPR‐02. Eleven QTLs in CPR‐01 and six QTLs in CPR‐02 populations were mapped on chromosomes Ca1, Ca2, Ca4, Ca6 and Ca7. The QTLs identified in CPR‐01 using conventional biparental mapping approach were used to compare the efficiency of NGS‐based BSA in detecting QTLs for ascochyta blight resistance. The QTLs on chromosomes Ca1, Ca4, Ca6 and Ca7 overlapped with the QTLs previously detected in CPR‐01 using conventional QTL mapping method. The QTLs on chromosome Ca4 were detected in both populations and overlapped with the previously reported QTLs indicating conserved region for ascochyta blight resistance across different chickpea genotypes. Six candidate genes in the QTL regions identified using NGS‐based BSA on chromosomes Ca2 and Ca4 were validated for their association with ascochyta blight resistance in the CPR‐02 population. This study demonstrated the efficiency of NGS‐based BSA as a rapid and cost‐effective method to identify QTLs associated with ascochyta blight in chickpea.     

How to optimize the precision of allele and haplotype frequency estimates using pooled‐sequencing data

Sequencing pools of individuals rather than individuals separately reduces the costs of estimating allele frequencies at many loci in many populations. Theoretical and empirical studies show that sequencing pools comprising a limited number of individuals (typically fewer than 50) provides reliable allele frequency estimates, provided that the DNA pooling and DNA sequencing steps are carefully controlled. Unequal contributions of different individuals to the DNA pool and the mean and variance in sequencing depth both can affect the standard error of allele frequency estimates. To our knowledge, no study separately investigated the effect of these two factors on allele frequency estimates; so that there is currently no method to a priori estimate the relative importance of unequal individual DNA contributions independently of sequencing depth. We develop a new analytical model for allele frequency estimation that explicitly distinguishes these two effects. Our model shows that the DNA pooling variance in a pooled sequencing experiment depends solely on two factors: the number of individuals within the pool and the coefficient of variation of individual DNA contributions to the pool. We present a new method to experimentally estimate this coefficient of variation when planning a pooled sequencing design where samples are either pooled before or after DNA extraction. Using this analytical and experimental framework, we provide guidelines to optimize the design of pooled sequencing experiments. Finally, we sequence replicated pools of inbred lines of the plant Medicago truncatula and show that the predictions from our model generally hold true when estimating the frequency of known multilocus haplotypes using pooled sequencing.     

Analysis and Optimization of Bulk DNA Sampling with Binary Scoring for Germplasm Characterization

The strategy of bulk DNA sampling has been a valuable method for studying large numbers of individuals through genetic markers. The application of this strategy for discrimination among germplasm sources was analyzed through information theory, considering the case of polymorphic alleles scored binarily for their presence or absence in DNA pools. We defined the informativeness of a set of marker loci in bulks as the mutual information between genotype and population identity, composed by two terms: diversity and noise. The first term is the entropy of bulk genotypes, whereas the noise term is measured through the conditional entropy of bulk genotypes given germplasm sources. Thus, optimizing marker information implies increasing diversity and reducing noise. Simple formulas were devised to estimate marker information per allele from a set of estimated allele frequencies across populations. As an example, they allowed optimization of bulk size for SSR genotyping in maize, from allele frequencies estimated in a sample of 56 maize populations. It was found that a sample of 30 plants from a random mating population is adequate for maize germplasm SSR characterization. We analyzed the use of divided bulks to overcome the allele dilution problem in DNA pools, and concluded that samples of 30 plants divided into three bulks of 10 plants are efficient to characterize maize germplasm sources through SSR with a good control of the dilution problem. We estimated the informativeness of 30 SSR loci from the estimated allele frequencies in maize populations, and found a wide variation of marker informativeness, which positively correlated with the number of alleles per locus.     

Evaluation of a DNA pooled-sampling strategy for estimating the RFLP diversity of maize populations

Molecular characterization by means of RFLPs of large sets of populations is presently limited by experimental costs. In order to reduce costs, we have evaluated a method based on the RFLP analysis of balanced bulks of DNA from several individuals. The precision of this approach for estimating allele frequencies within each population was investigated using (i) DNA extracted from controlled bulks of leaf tissues of maize inbred lines, (ii) data obtained from individual analyses of 10 maize populations. Both approaches showed that allele frequencies can generally be estimated with a high precision (coefficients of determination up to 0.99 for some probe-enzyme combinations assayed), relative to the variation in allele frequencies observed among maize populations. Although further efforts are needed to define a set of probe-enzyme combinations that can be routinely image processed, these results, and preliminary results from a 65 maize populations project, suggest that this approach could provide highly informative data for large sets of populations, and at relatively low costs.     

RAPD markers on seed bulks efficiently assess the genetic diversity of a Brassica oleracea L. collection

 The concept of a core collection was elaborated to fit the necessity of optimizing the management, for both conservation and use, of genetic resources in sizeable collections. This approach requires an analysis of how the genetic variability is structured among the accessions. The large number of heterogeneous populations in our collection of Brassica oleracea makes genetic diversity studies based on plant-to-plant analysis impracticable. To overcome this limitation, the variability analysis by RAPD on seed bulks was investigated for its efficiency in assessing the structure of the genetic diversity of this collection. The optimal bulk size and the bulking or sampling variation were evaluated with bulks of different size and with replicated samples. A mixture of known genotypes was also used to characterise the band detection in bulks, and to compare the plant-to-plant and the bulk methods. Forty seeds were chosen to represent each population. In such a bulk, the detection of bands depended on the proportion of the genotype they were derived from in the mixture. Intense and frequent bands were detected in the bulk with a 15% detection limit. The observed bulking or sampling variation within populations was smaller than the variation between populations, leading to an efficient separation of populations with a clustering of all samples of the same population. The distances calculated from bulk data were highly correlated with the distances based on the plant-to-plant analysis. We demonstrated that RAPD on seed bulks can be used to describe the genetic diversity between populations. Received: 27 August 1998 / Accepted: 29 September 1998     

SRAP Polymorphisms Associated to Cell Wall Degradability in Lignified Stems of Alfalfa

The identification of DNA polymorphisms associated to increased cell wall (CW) degradability could accelerate the development of alfalfa (Medicago sativa L.) cultivars with superior ethanol conversion yields. Genotypes with high (D+) or low (D?) CW degradability were recently identified within a biomass-type and three winter-hardy-type populations using near-infrared reflectance spectroscopy (NIRS) prediction of CW glucose released by enzyme saccharification. In this report, we used sequence-related amplified polymorphism to search for DNA variations associated to differences in enzyme-released glucose. A bulk segregant analysis (BSA) of pooled DNA samples (20 plants/bulk) from D+, D?, and randomly chosen genotypes uncovered polymorphisms associated to CW degradability. Polymorphisms that increase or decrease in intensity between D+ and D? bulks indicated the presence of genomic regions with either positive or negative effects on CW degradability. A primer pair (Me4-R14) generated a fragment, which increased in intensity in the D+ bulk of the biomass-type population. Conversely, the amplification of that fragment declined in the D+ bulks of the winter-hardy-type populations. Interestingly, these populations differ in their degradability. Assessment of the genotypic occurrence of this fragment confirmed that polymorphism detected with BSA reflects changes in the frequency of occurrence within populations. Sequence analysis of the Me4-R14 fragment revealed homologies with sequences from Medicago truncatula, a model species for legumes with documented synteny with M. sativa. Our results show that genomic regions associated to CW degradability can be identified using the combination of BSA of genotypes with contrasted degradability and a PCR-based amplification technique.     

Bulked sample analysis in genetics,genomics and crop improvement

Biological assay has been based on analysis of all individuals collected from sample populations. Bulked sample analysis (BSA), which works with selected and pooled individuals, has been extensively used in gene mapping through bulked segregant analysis with biparental populations, mapping by sequencing with major gene mutants and pooled genomewide association study using extreme variants. Compared to conventional entire population analysis, BSA significantly reduces the scale and cost by simplifying the procedure. The bulks can be built by selection of extremes or representative samples from any populations and all types of segregants and variants that represent wide ranges of phenotypic variation for the target trait. Methods and procedures for sampling, bulking and multiplexing are described. The samples can be analysed using individual markers, microarrays and high‐throughput sequencing at all levels of DNA, RNA and protein. The power of BSA is affected by population size, selection of extreme individuals, sequencing strategies, genetic architecture of the trait and marker density. BSA will facilitate plant breeding through development of diagnostic and constitutive markers, agronomic genomics, marker‐assisted selection and selective phenotyping. Applications of BSA in genetics, genomics and crop improvement are discussed with their future perspectives.     

Mapping multiple QTL of different effects: comparison of a simple sequential testing strategy and multiple QTL mapping

The aim of this study was to explore, by computer simulation, the mapping of QTLs in a realistic but complex situation of many (linked) QTLs with different effects, and to compare two QTL mapping methods. A novel method to dissect genetic variation on multiple chromosomes using molecular markers in backcross and F₂ populations derived from inbred lines was suggested, and its properties tested using simulations. The rationale for this sequential testing method was to explicitly test for alternative genetic models. The method consists of a series of four basic statistical tests to decide whether variance was due to a single QTL, two QTLs, multiple QTLs, or polygenes, starting with a test to detect genetic variance associated with a particular chromosome. The method was able to distinguish between different QTL configurations, in that the probability to `detect' the correct model was high, varying from 0.75 to 1. For example, for a backcross population of 200 and an overall heritability of 50%, in 78% of replicates a polygenic model was detected when that was the underlying true model. To test the method for multiple chromosomes, QTLs were simulated on 10 chromosomes, following a geometric series of allele effects, assuming positive alleles were in coupling in the founder lines For these simulations, the sequential testing method was compared to the established Multiple QTL Mapping (MQM) method. For a backcross population of 400 individuals, power to detect genetic variance was low with both methods when the heritability was 0.40. For example, the power to detect genetic variation on a chromosome on which 6 QTLs explained 12.6% of the genetic variance, was less than 60% for both methods. For a large heritability (0.90), the power of MQM to detect genetic variance and to dissect QTL configurations was generally better, due to the simultaneous fitting of markers on all chromosomes. It is concluded that when testing different QTL configurations on a single chromosome using the sequential testing procedure, regions of other chromosomes which explain a significant amount of variation should be fitted in the model of analysis. This study reinforces the need for large experiments in plants and other species if the aim of a genome scan is to dissect quantitative genetic variation.     

Hybrid incompatibility in Arabidopsis is determined by a multiple-locus genetic network

The cross between Arabidopsis thaliana and the closely related species Arabidopsis arenosa results in postzygotic hybrid incompatibility, manifested as seed death. Ecotypes of A. thaliana were tested for their ability to produce live seed when crossed to A. arenosa. The identified genetic variation was used to map quantitative trait loci (QTLs) encoded by the A. thaliana genome that affect the frequency of postzygotic lethality and the phenotypes of surviving seeds. Seven QTLs affecting the A. thaliana component of this hybrid incompatibility were identified by crossing a Columbia × C24 recombinant inbred line population to diploid A. arenosa pollen donors. Additional epistatic loci were identified based on their pairwise interaction with one or several of these QTLs. Epistatic interactions were detected for all seven QTLs. The two largest additive QTLs were subjected to fine-mapping, indicating the action of at least two genes in each. The topology of this network reveals a large set of minor-effect loci from the maternal genome controlling hybrid growth and viability at different developmental stages. Our study establishes a framework that will enable the identification and characterization of genes and pathways in A. thaliana responsible for hybrid lethality in the A. thaliana × A. arenosa interspecific cross.     

Accounting for genotype uncertainty in the estimation of allele frequencies in autopolyploids

Despite the increasing opportunity to collect large‐scale data sets for population genomic analyses, the use of high‐throughput sequencing to study populations of polyploids has seen little application. This is due in large part to problems associated with determining allele copy number in the genotypes of polyploid individuals (allelic dosage uncertainty–ADU), which complicates the calculation of important quantities such as allele frequencies. Here, we describe a statistical model to estimate biallelic SNP frequencies in a population of autopolyploids using high‐throughput sequencing data in the form of read counts. We bridge the gap from data collection (using restriction enzyme based techniques [e.g. GBS, RADseq]) to allele frequency estimation in a unified inferential framework using a hierarchical Bayesian model to sum over genotype uncertainty. Simulated data sets were generated under various conditions for tetraploid, hexaploid and octoploid populations to evaluate the model's performance and to help guide the collection of empirical data. We also provide an implementation of our model in the R package polyfreqs and demonstrate its use with two example analyses that investigate (i) levels of expected and observed heterozygosity and (ii) model adequacy. Our simulations show that the number of individuals sampled from a population has a greater impact on estimation error than sequencing coverage. The example analyses also show that our model and software can be used to make inferences beyond the estimation of allele frequencies for autopolyploids by providing assessments of model adequacy and estimates of heterozygosity.     

Fine Mapping QTL for Drought Resistance Traits in Rice (<Emphasis Type="Italic">Oryza sativa</Emphasis> L.) Using Bulk Segregant Analysis

Drought stress is a major limitation to rice (Oryza sativa L.) yields and its stability, especially in rainfed conditions. Developing rice cultivars with inherent capacity to withstand drought stress would improve rainfed rice production. Mapping quantitative trait loci (QTLs) linked to drought resistance traits will help to develop rice cultivars suitable for water-limited environments through molecular marker-assisted selection (MAS) strategy. However, QTL mapping is usually carried out by genotyping large number of progenies, which is labour-intensive, time-consuming and cost-ineffective. Bulk segregant analysis (BSA) serves as an affordable strategy for mapping large effect QTLs by genotyping only the extreme phenotypes instead of the entire mapping population. We have previously mapped a QTL linked to leaf rolling and leaf drying in recombinant inbred (RI) lines derived from two locally adapted indica rice ecotypes viz., IR20/Nootripathu using BSA. Fine mapping the QTL will facilitate its application in MAS. BSA was done by bulking DNA of 10 drought-resistant and 12 drought-sensitive RI lines. Out of 343 rice microsatellites markers genotyped, RM8085 co-segregated among the RI lines constituting the respective bulks. RM8085 was mapped in the middle of the QTL region on chromosome 1 previously identified in these RI lines thus reducing the QTL interval from 7.9 to 3.8 cM. Further, the study showed that the region, RM212–RM302–RM8085–RM3825 on chromosome 1, harbours large effect QTLs for drought-resistance traits across several genetic backgrounds in rice. Thus, the QTL may be useful for drought resistance improvement in rice through MAS and map-based cloning.     

Identification of RAPD markers linked to a fertility restorer gene for theOgura radish cytoplasmic male sterility of rapeseed (Brassica napus L.)

Bulked segregant analysis was employed to identify random amplified polymorphic DNA (RAPD) markers linked to the restorer gene (Rfo) used in theOgura radish cytoplasmic male sterility of rapeseed. A total of 138 arbitrary 10-mer oligonucleotide primers were screened on the DNA of three pairs of bulks, each bulk corresponding to homozygous restored and male sterile plants of three segregating populations. Six primers produced repeatable polymorphisms between paired bulks. DNA from individual plants of each bulk was then used as a template for amplification with these six primers. DNA polymorphisms generated by four of these primers were found to be completely linked to the restorer gene with the polymorphic DNA fragments being associated either with the fertility restorer allele or with the sterility maintainer allele. Pairwise cross-hybridization demonstrated that the four polymorphic DNA fragments did not share any homology. Southern hybridization of labelled RAPD fragments on digested genomic DNA from the same three pairs of bulks revealed fragments specific to either the male sterile bulks or to the restored bulks and a few fragments common to all bulks, indicating that the amplified sequences are low copy. The four RAPD fragments that were completely linked to the restorer locus have been cloned and sequenced to develop sequence characterized amplified regions (SCARs). This will facilitate the construction of restorer lines used in breeding programs and is the first step towards map-based cloning of the fertility restorer allele.     

Rare and common regulatory variation in population-scale sequenced human genomes

Population-scale genome sequencing allows the characterization of functional effects of a broad spectrum of genetic variants underlying human phenotypic variation. Here, we investigate the influence of rare and common genetic variants on gene expression patterns, using variants identified from sequencing data from the 1000 genomes project in an African and European population sample and gene expression data from lymphoblastoid cell lines. We detect comparable numbers of expression quantitative trait loci (eQTLs) when compared to genotypes obtained from HapMap 3, but as many as 80% of the top expression quantitative trait variants (eQTVs) discovered from 1000 genomes data are novel. The properties of the newly discovered variants suggest that mapping common causal regulatory variants is challenging even with full resequencing data; however, we observe significant enrichment of regulatory effects in splice-site and nonsense variants. Using RNA sequencing data, we show that 46.2% of nonsynonymous variants are differentially expressed in at least one individual in our sample, creating widespread potential for interactions between functional protein-coding and regulatory variants. We also use allele-specific expression to identify putative rare causal regulatory variants. Furthermore, we demonstrate that outlier expression values can be due to rare variant effects, and we approximate the number of such effects harboured in an individual by effect size. Our results demonstrate that integration of genomic and RNA sequencing analyses allows for the joint assessment of genome sequence and genome function.     

Failure to replicate two mate preference QTLs across multiple strains of Drosophila pseudoobscura

Behavioral genetic mapping studies in model organisms predominantly use crosses originating from a single pair of inbred lines to determine the location of alleles that confer genetic variation in the trait of interest, and they often make sweeping generalizations about the genetic architecture of the trait based on these results. A previous study fine mapped mate preference variation between one pair of Drosophila pseudoobscura lines and identified 2 strong-effect behavioral quantitative trait loci (QTLs). Here, we replicated the previous study's mapping design to examine the extent of variation at these behavioral QTLs across 6 pairs of lines, but we were unable to detect effects of either QTL region in the pairs of lines studied. We suggest that the low-discrimination alleles at these 2 QTLs may occur at low frequency within D. pseudoobscura, although other explanations for the inconsistency are possible. These results underscore the need to examine multiple strains across a species when describing the genetic variation underlying behavioral traits.     

Use of GBS markers to distinguish among lucerne varieties,with comparison to morphological traits

Variety registration of lucerne often fails because of the difficulty to pass the distinction test. This test is presently based on phenotypic traits. We proposed to evaluate if high-throughput genotyping of varieties with genotyping-by-sequencing markers could help to distinguish among 20 varieties and if the genetic distances were correlated to phenotypic ones. Genotyping was performed either on 40 individuals or on 4 bulks of 100 plants per variety. At the methodological level, we obtained a high number of polymorphic markers, a precise determination of the allele dosage on the individuals, a high reproducibility of allele frequency estimated on bulks and a good correlation between allele frequencies scored on individuals or on bulks. Each pair of the 20 varieties was significantly distinct when using the markers. In addition, the varieties grouped in a way that was consistent with their genetic origin. Genetic distances were correlated to phenotypic distances obtained from data collected in the distinction tests. We suggest that molecular markers could be useful to assist distinction tests during the official trials for registration of lucerne varieties.     

Novel linkage mapping approach using DNA pooling in human and animal genetics. II. Detection of quantitative traits loci in dairy cattle

Selective DNA pooling is an advanced methodology for linkage mapping of quantitative trait loci (QTL) in farm animals. The principle is based on densitometric estimates of marker allele frequency in pooled DNA samples of phenotypically extreme individuals from half-sib, backcross and F(2) experimental designs in farm animals. This methodology provides a rapid and efficient analysis of a large number of individuals with short tandem repeat markers that are essential to detect QTL through the genome - wide searching approach. Several strategies involving whole genome scanning with a high statistical power have been developed for systematic search to detect the quantitative traits loci and linked loci of complex traits. In recent studies, greater success has been achieved in mapping several QTLs in Israel-Holstein cattle using selective DNA pooling. This paper outlines the currently emerged novel strategies of linkage mapping to identify QTL based on selective DNA pooling with more emphasis on its theoretical pre-requisite to detect linked QTLs, applications, a general theory for experimental half-sib designs, the power of statistics and its feasibility to identify genetic markers linked QTL in dairy cattle. The study reveals that the application of selective DNA pooling in dairy cattle can be best exploited in the genome-wide detection of linked loci with small and large QTL effects and applied to a moderately sized half-sib family of about 500 animals.