Integrating sorghum whole genome sequence information with a compendium of sorghum QTL studies reveals uneven distribution of QTL and of gene-rich regions with significant implications for crop improvement

A comprehensive analysis was conducted using 48 sorghum QTL studies published from 1995 to 2010 to make information from historical sorghum QTL experiments available in a form that could be more readily used by sorghum researchers and plant breeders. In total, 771 QTL relating to 161 unique traits from 44 studies were projected onto a sorghum consensus map. Confidence intervals (CI) of QTL were estimated so that valid comparisons could be made between studies. The method accounted for the number of lines used and the phenotypic variation explained by individual QTL from each study. In addition, estimated centimorgan (cM) locations were calculated for the predicted sorghum gene models identified in Phytozome (JGI GeneModels SBI v1.4) and compared with QTL distribution genome-wide, both on genetic linkage (cM) and physical (base-pair/bp) map scales. QTL and genes were distributed unevenly across the genome. Heterochromatic enrichment for QTL was observed, with approximately 22% of QTL either entirely or partially located in the heterochromatic regions. Heterochromatic gene enrichment was also observed based on their predicted cM locations on the sorghum consensus map, due to suppressed recombination in heterochromatic regions, in contrast to the euchromatic gene enrichment observed on the physical, sequence-based map. The finding of high gene density in recombination-poor regions, coupled with the association with increased QTL density, has implications for the development of more efficient breeding systems in sorghum to better exploit heterosis. The projected QTL information described, combined with the physical locations of sorghum sequence-based markers and predicted gene models, provides sorghum researchers with a useful resource for more detailed analysis of traits and development of efficient marker-assisted breeding strategies.     

The genetic architecture of genome‐wide recombination rate variation in allopolyploid wheat revealed by nested association mapping

Recombination affects the fate of alleles in populations by imposing constraints on the reshuffling of genetic information. Understanding the genetic basis of these constraints is critical for manipulating the recombination process to improve the resolution of genetic mapping, and reducing the negative effects of linkage drag and deleterious genetic load in breeding. Using sequence‐based genotyping of a wheat nested association mapping (NAM) population of 2,100 recombinant inbred lines created by crossing 29 diverse lines, we mapped QTL affecting the distribution and frequency of 102 000 crossovers (CO). Genome‐wide recombination rate variation was mostly defined by rare alleles with small effects together explaining up to 48.6% of variation. Most QTL were additive and showed predominantly trans‐acting effects. The QTL affecting the proximal COs also acted additively without increasing the frequency of distal COs. We showed that the regions with decreased recombination carry more single nucleotide polymorphisms (SNPs) with possible deleterious effects than the regions with a high recombination rate. Therefore, our study offers insights into the genetic basis of recombination rate variation in wheat and its effect on the distribution of deleterious SNPs across the genome. The identified trans‐acting additive QTL can be utilized to manipulate CO frequency and distribution in the large polyploid wheat genome opening the possibility to improve the efficiency of gene pyramiding and reducing the deleterious genetic load in the low‐recombining pericentromeric regions of chromosomes.     

Meiotic Recombination, Noncoding DNA and Genomic Organization in Caenorhabditis Elegans

The genetic map of each Caenorhabditis elegans chromosome has a central gene cluster (less pronounced on the X chromosome) that contains most of the mutationally defined genes. Many linkage group termini also have clusters, though involving fewer loci. We examine the factors shaping the genetic map by analyzing the rate of recombination and gene density across the genome using the positions of cloned genes and random cDNA clones from the physical map. Each chromosome has a central gene-dense region (more diffuse on the X) with discrete boundaries, flanked by gene-poor regions. Only autosomes have reduced rates of recombination in these gene-dense regions. Cluster boundaries appear discrete also by recombination rate, and the boundaries defined by recombination rate and gene density mostly, but not always, coincide. Terminal clusters have greater gene densities than the adjoining arm but similar recombination rates. Thus, unlike in other species, most exchange in C. elegans occurs in gene-poor regions. The recombination rate across each cluster is constant and similar; and cluster size and gene number per chromosome are independent of the physical size of chromosomes. We propose a model of how this genome organization arose.     

Variation in recombination rate may bias human genetic disease mapping studies

The availability of the human genome sequence and variability information (as from the International HapMap project) will enhance our ability to map genetic disorders and choose targets for therapeutic intervention. However, several factors, such as regional variation in recombination rate, can bias conclusions from genetic mapping studies. Here, we examine the impact of regional variation in recombination rate across the human genome. Through computer simulations and literature surveys, we conclude that genetic disorders have been mapped to regions of low recombination more often than expected if such diseases were randomly distributed across the genome. This concentration in low recombination regions may be an artifact, and disorders appearing to be caused by a few genes of large effect may be polygenic. Future genetic mapping studies should be conscious of this potential complication by noting the regional recombination rate of regions implicated in diseases.     

Mapping of homoeologous chromosome exchanges influencing quantitative trait variation in Brassica napus

Genomic rearrangements arising during polyploidization are an important source of genetic and phenotypic variation in the recent allopolyploid crop Brassica napus. Exchanges among homoeologous chromosomes, due to interhomoeologue pairing, and deletions without compensating homoeologous duplications are observed in both natural B. napus and synthetic B. napus. Rearrangements of large or small chromosome segments induce gene copy number variation (CNV) and can potentially cause phenotypic changes. Unfortunately, complex genome restructuring is difficult to deal with in linkage mapping studies. Here, we demonstrate how high‐density genetic mapping with codominant, physically anchored SNP markers can detect segmental homoeologous exchanges (HE) as well as deletions and accurately link these to QTL. We validated rearrangements detected in genetic mapping data by whole‐genome resequencing of parental lines along with cytogenetic analysis using fluorescence in situ hybridization with bacterial artificial chromosome probes (BAC‐FISH) coupled with PCR using primers specific to the rearranged region. Using a well‐known QTL region influencing seed quality traits as an example, we confirmed that HE underlies the trait variation in a DH population involving a synthetic B. napus trait donor, and succeeded in narrowing the QTL to a small defined interval that enables delineation of key candidate genes.     

QTL mapping reveals the genetic architecture of loci affecting pre- and post-zygotic isolating barriers in Louisiana Iris

ABSTRACT: BACKGROUND: Hybridization among Louisiana Irises has been well established and the genetic architecture of reproductive isolation is known to affect the potential for and the directionality of introgression between taxa. Here we use co-dominant markers to identify regions where QTL are located both within and between backcross maps to compare the genetic architecture of reproductive isolation and fitness traits across treatments and years. RESULTS: QTL mapping was used to elucidate the genetic architecture of reproductive isolation between Iris fulva and Iris brevicaulis. Homologous co-dominant EST-SSR markers scored in two backcross populations between I. fulva and I. brevicaulis were used to generate genetic linkage maps. These were used as the framework for mapping QTL associated with variation in 11 phenotypic traits likely responsible for reproductive isolation and fitness. QTL were dispersed throughout the genome, with the exception of one region of a single linkage group (LG) where QTL for flowering time, sterility, and fruit production clustered. In most cases, homologous QTL were not identified in both backcross populations, however, homologous QTL for flowering time, number of growth points per rhizome, number of nodes per inflorescence, and number of flowers per node were identified on several linkage groups. CONCLUSION: Two different traits affecting reproductive isolation, flowering time and sterility, exhibit different genetic architectures, with numerous QTL across the Iris genome controlling flowering time and fewer, less distributed QTL affecting sterility. QTL for traits affecting fitness are largely distributed across the genome with occasional overlap, especially on LG 4, where several QTL increasing fitness and decreasing sterility cluster. Given the distribution and effect direction of QTL affecting reproductive isolation and fitness, we have predicted genomic regions where introgression may be more likely to occur (those regions associated with an increase in fitness and unlinked to loci controlling reproductive isolation) and those that are less likely to exhibit introgression (those regions linked to traits decreasing fitness and reproductive isolation).     

Major quantitative trait loci affect resistance to infectious pancreatic necrosis in Atlantic salmon (Salmo salar)

Infectious pancreatic necrosis (IPN) is a viral disease currently presenting a major problem in the production of Atlantic salmon (Salmon salar). IPN can cause significant mortality to salmon fry within freshwater hatcheries and to smolts following transfer to seawater, although challenged populations show clear genetic variation in resistance. To determine whether this genetic variation includes loci of major effect, a genomewide quantitative trait loci (QTL) scan was performed within 10 full-sib families that had received a natural seawater IPN challenge. To utilize the large difference between Atlantic salmon male and female recombination rates, a two-stage mapping strategy was employed. Initially, a sire-based QTL analysis was used to detect linkage groups with significant effects on IPN resistance, using two to three microsatellite markers per linkage group. A dam-based analysis with additional markers was then used to confirm and position any detected QTL. Two genomewide significant QTL and one suggestive QTL were detected in the genome scan. The most significant QTL was mapped to linkage group 21 and was significant at the genomewide level in both the sire and the dam-based analyses. The identified QTL can be applied in marker-assisted selection programs to improve the resistance of salmon to IPN and reduce disease-related mortality.     

High recombination rates and hotspots in a Plasmodium falciparum genetic cross

Background

The human malaria parasite Plasmodium falciparum survives pressures from the host immune system and antimalarial drugs by modifying its genome. Genetic recombination and nucleotide substitution are the two major mechanisms that the parasite employs to generate genome diversity. A better understanding of these mechanisms may provide important information for studying parasite evolution, immune evasion and drug resistance.

Results

Here, we used a high-density tiling array to estimate the genetic recombination rate among 32 progeny of a P. falciparum genetic cross (7G8 × GB4). We detected 638 recombination events and constructed a high-resolution genetic map. Comparing genetic and physical maps, we obtained an overall recombination rate of 9.6 kb per centimorgan and identified 54 candidate recombination hotspots. Similar to centromeres in other organisms, the sequences of P. falciparum centromeres are found in chromosome regions largely devoid of recombination activity. Motifs enriched in hotspots were also identified, including a 12-bp G/C-rich motif with 3-bp periodicity that may interact with a protein containing 11 predicted zinc finger arrays.

Conclusions

These results show that the P. falciparum genome has a high recombination rate, although it also follows the overall rule of meiosis in eukaryotes with an average of approximately one crossover per chromosome per meiosis. GC-rich repetitive motifs identified in the hotspot sequences may play a role in the high recombination rate observed. The lack of recombination activity in centromeric regions is consistent with the observations of reduced recombination near the centromeres of other organisms.     

Recombination rates across porcine autosomes inferred from high-density linkage maps

Studies of the variation in recombination rate across the genome provide a better understanding of evolutionary genomics and are also an important step towards mapping and dissecting complex traits in domestic animals. With the recent completion of the porcine genome sequence and the availability of a high‐density porcine single nucleotide polymorphism (SNP) array, it is now possible to construct a high‐density porcine linkage map and estimate recombination rate across the genome. A total of 416 animals were genotyped with the Porcine SNP60BeadChip, and high‐density chromosome linkage maps were constructed using CRI‐MAP, assuming the physical order of the Sscrofa10 assembly. The total linkage map length was 2018.79 cM, using 658 meioses and 14 503 SNPs. The estimated average recombination rate across the porcine autosomes was 0.86 cM/Mb. However, a large variation in recombination rate was observed among chromosomes. The estimated average recombination rates (cM/Mb) per chromosome ranged from 0.48 in SSC1 to 1.48 in SSC10, displaying a significant negative correlation with the chromosome sizes. In addition, the analysis of the variation in the recombination rates taking 1‐Mb sliding windows has allowed us to demonstrate the variation in recombination rates within chromosomes. In general, a larger recombination rate was observed in the extremes than in the centre of the chromosome. Finally, the ratio between female and male recombination rates was also inferred, obtaining a value of 1.38, with the heterogametic sex having the least recombination.     

A dense linkage map of hybrid cottonwood (Populus fremontii x P. angustifolia) contributes to long-term ecological research and comparison mapping in a model forest tree

Cottonwoods are foundation riparian species, and hybridization among species is known to produce ecological effects at levels higher than the population, including effects on dependent species, communities and ecosystems. Because these patterns result from increased genetic variation in key cottonwood traits, novel applications of genetic tools (for example, QTL mapping) could be used to place broad-scale ecological research into a genomic perspective. In addition, linkage maps have been produced for numerous species within the genus, and, coupled with the recent publication of the Populus genome sequence, these maps present a unique opportunity for genome comparisons in a model system. Here, we conducted linkage analyses in order to (1) create a platform for QTL and candidate gene studies of ecologically important traits, (2) create a framework for chromosomal-scale perspectives of introgression in a natural population, and (3) enhance genome-wide comparisons using two previously unmapped species. We produced 246 backcross mapping (BC(1)) progeny by crossing a naturally occurring F(1) hybrid (Populus fremontii x P. angustifolia) to a pure P. angustifolia from the same population. Linkage analysis resulted in a dense linkage map of 541 AFLP and 111 SSR markers distributed across 19 linkage groups. These results compared favorably with other Populus linkage studies, and addition of SSR loci from the poplar genome project provided coarse alignment with the genome sequence. Preliminary applications of the data suggest that our map represents a useful framework for applying genomic research to ecological questions in a well-studied system, and has enhanced genome-wide comparisons in a model tree.     

A plant-transformation-competent BIBAC/BAC-based map of rice for functional analysis and genetic engineering of its genomic sequence.

Sequencing of the rice genome has provided a platform for functional genomics research of rice and other cereal species. However, multiple approaches are needed to determine the functions of its genes and sequences and to use the genome sequencing results for genetic improvement of cereal crops. Here, we report a plant-transformation-competent, binary bacterial artificial chromosome (BIBAC) and bacterial artificial chromosome (BAC) based map of rice to facilitate these studies. The map was constructed from 20 835 BIBAC and BAC clones, and consisted of 579 overlapping BIBAC/BAC contigs. To facilitate functional analysis of chromosome 8 genomic sequence and cloning of the genes and QTLs mapped to the chromosome, we anchored the chromosomal contigs to the existing rice genetic maps. The chromosomal map consists of 11 contigs, 59 genetic markers, and 36 sequence tagged sites, spanning a total of ca. 38 Mb in physical length. Comparative analysis between the genetic and physical maps of chromosome 8 showed that there are 3 "hot" and 2 "cold" spots of genetic recombination along the chromosomal arms in addition to the "cold spot" in the centromeric region, suggesting that the sequence component contents of a chromosome may affect its local genetic recombination frequencies. Because of its plant transformability, the BIBAC/BAC map could provide a platform for functional analysis of the rice genome sequence and effective use of the sequencing results for gene and QTL cloning and molecular breeding.     

Genome-Wide Association Mapping for Yield and Other Agronomic Traits in an Elite Breeding Population of Tropical Rice (Oryza sativa)

Genome-wide association mapping studies (GWAS) are frequently used to detect QTL in diverse collections of crop germplasm, based on historic recombination events and linkage disequilibrium across the genome. Generally, diversity panels genotyped with high density SNP panels are utilized in order to assay a wide range of alleles and haplotypes and to monitor recombination breakpoints across the genome. By contrast, GWAS have not generally been performed in breeding populations. In this study we performed association mapping for 19 agronomic traits including yield and yield components in a breeding population of elite irrigated tropical rice breeding lines so that the results would be more directly applicable to breeding than those from a diversity panel. The population was genotyped with 71,710 SNPs using genotyping-by-sequencing (GBS), and GWAS performed with the explicit goal of expediting selection in the breeding program. Using this breeding panel we identified 52 QTL for 11 agronomic traits, including large effect QTLs for flowering time and grain length/grain width/grain-length-breadth ratio. We also identified haplotypes that can be used to select plants in our population for short stature (plant height), early flowering time, and high yield, and thus demonstrate the utility of association mapping in breeding populations for informing breeding decisions. We conclude by exploring how the newly identified significant SNPs and insights into the genetic architecture of these quantitative traits can be leveraged to build genomic-assisted selection models.     

The Power of QTL Mapping with RILs

QTL (quantitative trait loci) mapping is commonly used to identify genetic regions responsible to important phenotype variation. A common strategy of QTL mapping is to use recombinant inbred lines (RILs), which are usually established by several generations of inbreeding of an F1 population (usually up to F6 or F7 populations). As this inbreeding process involves a large amount of labor, we are particularly interested in the effect of the number of inbreeding generations on the power of QTL mapping; a part of the labor could be saved if a smaller number of inbreeding provides sufficient power. By using simulations, we investigated the performance of QTL mapping with recombinant inbred lines (RILs). As expected, we found that the power of F4 population could be almost comparable to that of F6 and F7 populations. A potential problem in using F4 population is that a large proportion of RILs are heterozygotes. We here introduced a new method to partly relax this problem. The performance of this method was verified by simulations with a wide range of parameters including the size of the segregation population, recombination rate, genome size and the density of markers. We found our method works better than the commonly used standard method especially when there are a number of heterozygous markers. Our results imply that in most cases, QTL mapping does not necessarily require RILs at F6 or F7 generations; rather, F4 (or even F3) populations would be almost as useful as F6 or F7 populations. Because the cost to establish a number of RILs for many generations is enormous, this finding will cause a reduction in the cost of QTL mapping, thereby accelerating gene mapping in many species.     

A Contiguous Physical Map of the Pericentromeric Region of Chromosome 21q between D21Z1 and D21S13E

We constructed a long range restriction map of the pericentromeric 21q region between the centromere, identified by the alphoid DNA sequence D21Z1, and D21S13E. The physical map showed the order and intermarker distances of five new loci, including two for which highly informative dinucleotide repeat polymorphisms were identified. The total distance between D21Z1 and D21S13E was 2400 kb. Comparison of genetic and physical distances indicated that there is about 400 to 500 kb per centimorgan that is not significantly different from the average 470 kb per centimorgan for the whole of chromosome 21q. Our physical mapping results do not indicate suppression of recombination in pericentromeric 21q.     

Do large effect QTL fractionate? A case study at the maize domestication QTL teosinte branched1

Quantitative trait loci (QTL) mapping is a valuable tool for studying the genetic architecture of trait variation. Despite the large number of QTL studies reported in the literature, the identified QTL are rarely mapped to the underlying genes and it is usually unclear whether a QTL corresponds to one or multiple linked genes. Similarly, when QTL for several traits colocalize, it is usually unclear whether this is due to the pleiotropic action of a single gene or multiple linked genes, each affecting one trait. The domestication gene teosinte branched1 (tb1) was previously identified as a major domestication QTL with large effects on the differences in plant and ear architecture between maize and teosinte. Here we present the results of two experiments that were performed to determine whether the single gene tb1 explains all trait variation for its genomic region or whether the domestication QTL at tb1 fractionates into multiple linked QTL. For traits measuring plant architecture, we detected only one QTL per trait and these QTL all mapped to tb1. These results indicate that tb1 is the sole gene for plant architecture traits that segregates in our QTL mapping populations. For most traits related to ear morphology, we detected multiple QTL per trait in the tb1 genomic region, including a large effect QTL at tb1 itself plus one or two additional linked QTL. tb1 is epistatic to two of these additional QTL for ear traits. Overall, these results provide examples for both a major QTL that maps to a single gene, as well as a case in which a QTL fractionates into multiple linked QTL.     

Punctuated Distribution of Recombination Hotspots and Demarcation of Pericentromeric Regions in Phaseolus vulgaris L.

High density genetic maps are a reliable tool for genetic dissection of complex plant traits. Mapping resolution is often hampered by the variable crossover and non-crossover events occurring across the genome, with pericentromeric regions (pCENR) showing highly suppressed recombination rates. The efficiency of linkage mapping can further be improved by characterizing and understanding the distribution of recombinational activity along individual chromosomes. In order to evaluate the genome wide recombination rate in common beans (Phaseolus vulgaris L.) we developed a SNP-based linkage map using the genotype-by-sequencing approach with a 188 recombinant inbred line family generated from an inter gene pool cross (Andean x Mesoamerican). We identified 1,112 SNPs that were subsequently used to construct a robust linkage map with 11 groups, comprising 513 recombinationally unique marker loci spanning 943 cM (LOD 3.0). Comparative analysis showed that the linkage map spanned >95% of the physical map, indicating that the map is almost saturated. Evaluation of genome-wide recombination rate indicated that at least 45% of the genome is highly recombinationally suppressed, and allowed us to estimate locations of pCENRs. We observed an average recombination rate of 0.25 cM/Mb in pCENRs as compared to the rest of genome that showed 3.72 cM/Mb. However, several hot spots of recombination were also detected with recombination rates reaching as high as 34 cM/Mb. Hotspots were mostly found towards the end of chromosomes, which also happened to be gene-rich regions. Analyzing relationships between linkage and physical map indicated a punctuated distribution of recombinational hot spots across the genome.     

Multiparent intercross populations in analysis of quantitative traits

Most traits of interest to medical, agricultural and animal scientists show continuous variation and complex mode of inheritance. DNA-based markers are being deployed to analyse such complex traits, that are known as quantitative trait loci (QTL). In conventional QTL analysis, F2, backcross populations, recombinant inbred lines, backcross inbred lines and double haploids from biparental crosses are commonly used. Introgression lines and near isogenic lines are also being used for QTL analysis. However, such populations have major limitations like predominantly relying on the recombination events taking place in the F1 generation and mapping of only the allelic pairs present in the two parents. The second generation mapping resources like association mapping, nested association mapping and multiparent intercross populations potentially address the major limitations of available mapping resources. The potential of multiparent intercross populations in gene mapping has been discussed here. In such populations both linkage and association analysis can be conductted without encountering the limitations of structured populations. In such populations, larger genetic variation in the germplasm is accessed and various allelic and cytoplasmic interactions are assessed. For all practical purposes, across crop species, use of eight founders and a fixed population of 1000 individuals are most appropriate. Limitations with multiparent intercross populations are that they require longer time and more resource to be generated and they are likely to show extensive segregation for developmental traits, limiting their use in the analysis of complex traits. However, multiparent intercross population resources are likely to bring a paradigm shift towards QTL analysis in plant species.