Fine mapping and imprinting analysis for fatness trait QTLs in pigs

Quantitative trait loci (QTL) for fatness traits were reported recently in an experimental Meishan × Large White and Landrace F₂ cross. To further investigate the regions on pig Chr 2 (SSC2), SSC4, and SSC7, 25 additional markers from these regions were typed on 800 animals (619 F₂ animals, their F₁ parents, and F₀ grandfathers). Compared with the published maps, a modified order of markers was observed for SSC4 and SSC7. QTL analyses were performed both within the half-sib families as well as across families (line cross). Furthermore, a QTL model accounting for imprinting effects was tested. Information content could be increased considerably on all three chromosomes. Evidence for the backfat thickness QTL on SSC7 was increased, and the location could be reduced to a 33-cM confidence interval. The QTL for intramuscular fat on SSC4 could not be detected in this half-sib analysis, whereas under the line cross model a suggestive QTL on a different position on SSC4 was detected. For SSC2, in the half-sib analysis, a suggestive QTL for backfat thickness was detected with the best position at 26 cM. Imprinting analysis, however, revealed a genome-wise, significant, paternally expressed QTL on SSC2 with the best position at 63 cM. Our results suggest that this QTL is different from the previously reported paternally expressed QTL for muscle mass and fat deposition on the distal tip of SSC2p. Received: 15 October 1999 / Accepted: 21 February 2000     

Fine mapping QTL for female fertility on BTA04 and BTA13 in dairy cattle using HD SNP and sequence data

Background

Female fertility is important for the maintenance of the production in a dairy cattle herd. Two QTL regions on BTA04 and on BTA13 previously detected in Nordic Holstein (NH) and validated in the Danish Jersey (DJ) and Nordic Red (NR) were investigated further in the present study to further refine the QTL locations. Refined QTL regions were imputed to the full sequence data. The genes in the regions were then studied to ascertain their possible effect on fertility traits.

Results

BTA04 was screened for number of inseminations (AIS), 56-day non-return rate (NRR), days from first to last insemination (IFL), and the interval from calving to first insemination (ICF) in the range of 38,257,758 to 40,890,784 bp, whereas BTA13 was screened for ICF only in the range from 21,236,959 to 46,150,079 with the HD bovine SNP array for NH, DJ and NR. No markers in the DJ and NR breeds reached significance. By analyzing imputed sequence data the QTL position on BTA04 was narrowed down to two regions in the NH. In these two regions a total of 9 genes were identified. BTA13 was analyzed using sequence data for the NH breed. The highest –log₁₀(P-value) was 19.41 at 33,903,159 bp. Two regions were identified: Region 1: 33,900,143-33,908,994 bp and Region 2: 34,051,815-34,056,728 bp. SNPs within and between these two regions were annotated as intergenic.

Conclusion

Screening BTA04 and BTA13 for female fertility traits in NH, NR and DJ suggested that the QTL for female fertility were specific for NH. A missense mutation in CD36 showed the strongest association with fertility traits on BTA04. The annotated SNPs on BTA13 were all intergenic variants. It is possible that BTA13 at this stage is poorly annotated such that the associated polymorphisms are located in as-yet undiscovered genes. Fertility traits are complex traits as many different biological and physiological factors determine whether a cow is fertile. Therefore it is not expected that there is a simple explanation with an obvious candidate gene but it is more likely a network of genes and intragenic variants that explain the variation of these traits.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-790) contains supplementary material, which is available to authorized users.     

Fine mapping of copy number variations on two cattle genome assemblies using high density SNP array

ABSTRACT: BACKGROUND: Btau_4.0 and UMD3.1 are two distinct cattle reference genome assemblies. In our previous study using the low density BovineSNP50 array, we reported a copy number variation (CNV) analysis on Btau_4.0 with 521 animals of 21 cattle breeds, yielding 682 CNV regions with a total length of 139.8 megabases. RESULTS: In this study using the high density BovineHD SNP array, we performed high resolution CNV analyses on both Btau_4.0 and UMD3.1 with 674 animals of 27 cattle breeds. We first compared CNV results derived from these two different SNP array platforms on Btau_4.0. With two thirds of the animals shared between studies, on Btau_4.0 we identified 3,346 candidate CNV regions representing 142.7 megabases (~4.70%) of the genome. With a similar total length but 5 times more event counts, the average CNVR length of current Btau_4.0 dataset is significantly shorter than the previous one (42.7kb vs. 205 kb). Although subsets of these two results overlapped, 64% (91.6 megabases) of current dataset was not present in the previous study. We also performed similar analyses on UMD3.1 using these BovineHD SNP array results. Approximately 50% more and 20% longer CNVs were called on UMD3.1 as compared to those on Btau_4.0. However, a comparable result of CNVRs (3,438 regions with a total length 146.9 megabases) was obtained. We suspect that these results are due to that UMD3.1's efforts of placing unplaced contigs and removing unmerged alleles. Selected CNVs were further experimentally validated, achieving a 73% PCR validation rate, which is considerably higher than the previous validation rate. About 20-45% of CNV regions overlapped with cattle RefSeq genes and Ensembl genes. Panther and IPA analyses indicated that these genes provide a wide spectrum of biological processes involving immune system, lipid metabolism, cell, organism and system development. CONCLUSION: We present a comprehensive result of cattle CNVs at a higher resolution and sensitivity. We identified over 3,000 candidate CNV regions on both Btau_4.0 and UMD3.1, further compared current datasets with previous results, and examined the impacts of genome assemblies on CNV calling.     

Identity by descent mapping of founder mutations in cancer using high-resolution tumor SNP data

Dense genotype data can be used to detect chromosome fragments inherited from a common ancestor in apparently unrelated individuals. A disease-causing mutation inherited from a common founder may thus be detected by searching for a common haplotype signature in a sample population of patients. We present here FounderTracker, a computational method for the genome-wide detection of founder mutations in cancer using dense tumor SNP profiles. Our method is based on two assumptions. First, the wild-type allele frequently undergoes loss of heterozygosity (LOH) in the tumors of germline mutation carriers. Second, the overlap between the ancestral chromosome fragments inherited from a common founder will define a minimal haplotype conserved in each patient carrying the founder mutation. Our approach thus relies on the detection of haplotypes with significant identity by descent (IBD) sharing within recurrent regions of LOH to highlight genomic loci likely to harbor a founder mutation. We validated this approach by analyzing two real cancer data sets in which we successfully identified founder mutations of well-characterized tumor suppressor genes. We then used simulated data to evaluate the ability of our method to detect IBD tracts as a function of their size and frequency. We show that FounderTracker can detect haplotypes of low prevalence with high power and specificity, significantly outperforming existing methods. FounderTracker is thus a powerful tool for discovering unknown founder mutations that may explain part of the "missing" heritability in cancer. This method is freely available and can be used online at the FounderTracker website.     

Fine structure mapping of the barley chromosome-1 centromere region containing malting-quality QTLs

 Current techniques for quantitative trait locus (QTLs) analyses provide only approximate locations of QTLs on chromosomes. Further resolution of identified QTL regions is often required for detailed characterization. An important region containing malting-quality QTLs on barley (Hordeum vulgare L.) chromosome 1 was identified by previous QTL analyses in a Steptoe×Morex cross. This region contains two putative adjacent overlapping QTLs, each of which has effects on malt-extract percentage, α-amylase activity, diastatic power, and malt β-glucan content. All favorable alleles for these traits are attributed to Morex. The objective of the present study was fine structure mapping of this complex QTL region to elucidate whether these two putative overlapping QTLs are really one QTL. Another question was whether the apparently overlapping QTLs are due to the pleiotropic effects of a single gene, or the independent effects of several genes. A high-resolution map in the target region was developed which spans approximately 27 cM. Molecular-marker-assisted backcrossing was employed to create isogenic lines with a Steptoe background differing only in the region containing the QTLs of interest. A total of 32 different recombinants were identified, of which eight most-informative isogenic lines plus one reconstructed Steptoe control were selected for field testing. The additive effects on malt-extract percentage, α-amylase activity, diastatic power, and malt β-glucan content from eight isogenic lines were calculated based on malting data from three locations. By comparing the significant additive effects among isogenic lines carrying different Morex fragments, two QTLs each for malt extract and for α-amylase, and two to three for diastatic power were identified in certain environments and resolved into 1–8-cM genome fragments. There was a significant QTL×environment interaction for diastatic power, and there are indications that epistatic interactions for malt β-glucan content occur between the QTLs on chromosome 1 and QTLs on other chromosomes. Received : 4 June 1997 / Accepted : 19 June 1997     

Genetic mapping of folate QTLs using a segregated population in maizeFA

As essential B vitamin for humans, folates accumulation in edible parts of crops, such as maize kernels, is of great importance for human health. But its breeding is always limited by the prohibitive cost of folate profiling. The molecular breeding is a more executable and efficient way for folate fortification, but is limited by the molecular knowledge of folate regulation. Here we report the genetic mapping of folate quantitative trait loci(QTLs) using a segregated population crossed by two maize lines, one high in folate(GEMS31) and the other low in folate(DAN3130). Two folate QTLs on chromosome 5 were obtained by the combination of F_2 whole-exome sequencing and F_3 kernel-folate profiling. These two QTLs had been confirmed by bulk segregant analysis using F_6 pooled DNA and F_7 kernel-folate profiling, and were overlapped with QTLs identified by another segregated population. These two QTLs contributed 41.6% of phenotypic variation of 5-formyltetrahydrofolate, the most abundant storage form among folate derivatives in dry maize grains, in the GEMS31 DAN3130 population.Their fine mapping and functional analysis will reveal details of folate metabolism, and provide a basis for marker-assisted breeding aimed at the enrichment of folates in maize kernels.     

Fine genetic characterization of elite maize germplasm using high-throughput SNP genotyping

To investigate the genetic structure of Chinese maize germplasm, the MaizeSNP50 BeadChip with 56,110 single nucleotide polymorphisms (SNPs) was used to genotype a collection of 367 inbred lines widely used in maize breeding of China. A total of 41,819 informative SNPs with minor allele number of more than 0.05 were used to estimate the genetic diversity, relatedness, and linkage disequilibrium (LD) decay. Totally 1,015 SNPs evenly distributed in the genome were selected randomly to evaluate the population structure of these accessions. Results showed that two main groups could be determined i.e., the introduced germplasm and the local germplasm. Further, five subgroups corresponding to different heterotic groups, that is, Reid Yellow Dent (Reid), Lancaster Sure Crop (Lancaster), P group (P), Tang Sipingtou (TSPT), and Tem-tropic I group (Tem-tropic I), were determined. The genetic diversity of within subgroups was highest in the Tem-Tropic I and lowest in the P. Most lines in this panel showed limited relatedness with each other. Comparisons of gene diversity showed that there existed some conservative genetic regions in specific subgroups across the ten chromosomes, i.e., seven in the Lancaster, seven in the Reid, six in the TSPT, five in the P, and two in the Tem-Tropical I. In addition, the results also revealed that there existed fifteen conservative regions transmitted from Huangzaosi, an important foundation parent, to its descendants. These are important for further studies since the outcomes may provide clues to understand why Huangzaosi could become a foundation parent in Chinese maize breeding. For the panel of 367 elite lines, average LD distance was 391 kb and varied among different chromosomes as well as in different genomic regions of one chromosome. This analysis uncovered a high natural genetic diversity in the elite maize inbred set, suggesting that the panel can be used in association study, esp. for temperate regions.     

Rapid SNP discovery and genetic mapping using sequenced RAD markers

Single nucleotide polymorphism (SNP) discovery and genotyping are essential to genetic mapping. There remains a need for a simple, inexpensive platform that allows high-density SNP discovery and genotyping in large populations. Here we describe the sequencing of restriction-site associated DNA (RAD) tags, which identified more than 13,000 SNPs, and mapped three traits in two model organisms, using less than half the capacity of one Illumina sequencing run. We demonstrated that different marker densities can be attained by choice of restriction enzyme. Furthermore, we developed a barcoding system for sample multiplexing and fine mapped the genetic basis of lateral plate armor loss in threespine stickleback by identifying recombinant breakpoints in F(2) individuals. Barcoding also facilitated mapping of a second trait, a reduction of pelvic structure, by in silico re-sorting of individuals. To further demonstrate the ease of the RAD sequencing approach we identified polymorphic markers and mapped an induced mutation in Neurospora crassa. Sequencing of RAD markers is an integrated platform for SNP discovery and genotyping. This approach should be widely applicable to genetic mapping in a variety of organisms.     

Assessment of DNA pooling strategies for mapping of QTLs

The synthesis of DNA pools from segregating populations is an efficient strategy for identifying DNA markers closely linked to genes or genomic regions of interest. To-date, DNA pooling based solely upon phenotypic information, or bulked segregant analysis, has been employed only in the analysis of simply-inherited traits. We have assessed the utility of phenotype-based DNA pools for tagging (e.g., identifying DNA markers closely-linked to) quantitative trait loci (QTLs), segregating in the presence of other such loci, and expressing phenotypes which are influenced by the environment. Theoretical estimates suggest that QTL alleles with phenotypic effects of 0.75–1.0 standard deviations (SD), or larger, should be detectable in back-cross (BC), F₂ and recombinant inbred (RI) or doubled haploid (DH) populations of manageable size (100–200 plants/lines). However, post hoc analysis of three data sets, used in QTL mapping of tomato and rice, indicate that the majority of QTLs identified had allele effects of less than 0.75 SD, and thus could not be easily tagged in DNA pools. Segregation distortion can have a large effect on the allelic composition of DNA pools, necessitating the use of more individuals in the pools to minimize false positive and false negative results. In general, we suggest that use of phenotype-based DNA pools might be successful in tagging QTLs of very large effect, but is unlikely to permit comprehensive identification of the majority of QTLs affecting a complex trait. DNA pools constructed from a priori information should, however, be useful in identifying new DNA markers for regions of the genome known to contain QTLs.     

Quantitative Trait Loci (QTLs) mapping for growth traits in the mouse: A review

The attainment of a specific mature body size is one of the most fundamental differences among species of mammals. Moreover, body size seems to be the central factor underlying differences in traits such as growth rate, energy metabolism and body composition. An important proportion of this variability is of genetic origin. The goal of the genetic analysis of animal growth is to understand its "genetic architecture", that is the number and position of loci affecting the trait, the magnitude of their effects, allele frequencies and types of gene action. In this review, the different strategies developed to identify and characterize genes involved in the regulation of growth in the mouse are described, with emphasis on the methods developed to map loci contributing to the regulation of quantitative traits (QTLs).     

Fine mapping of QTLs for rice grain yield under drought reveals sub-QTLs conferring a response to variable drought severities

Fine-mapping studies on four QTLs, qDTY(2.1), qDTY(2.2), qDTY(9.1) and qDTY(12.1), for grain yield (GY) under drought were conducted using four different backcross-derived populations screened in 16 experiments from 2006 to 2010. Composite and bayesian interval mapping analyses resolved the originally identified qDTY(2.1) region of 42.3 cM into a segment of 1.6 cM, the qDTY(2.2) region of 31.0 cM into a segment of 6.7 cM, the qDTY(9.1) region of 32.1 cM into two segments of 9.4 and 2.4 cM and the qDTY(12.1) region of 10.6 cM into two segments of 3.1 and 0.4 cM. Two of the four QTLs (qDTY(9.1) and qDTY(12.1)) having effects under varying degrees of stress severity showed the presence of more than one region within the original QTL. The study found the presence of a donor allele at RM262 within qDTY(2.1) and RM24334 within qDTY(9.1) showing a negative effect on GY under drought, indicating the necessity of precise fine mapping of QTL regions before using them in marker-assisted selection (MAS). However, the presence of sub-QTLs together in close vicinity to each other provides a unique opportunity to breeders to introgress such regions together as a unit into high-yielding drought-susceptible varieties through MAS.     

Analysis of wilms tumors using SNP mapping array-based comparative genomic hybridization

Wilms tumor (WT) has been a model to study kidney embryogenesis and tumorigenesis and, although associated with hereditary, cancer predisposition syndromes, the majority of tumors occur sporadically. To analyze genetic changes in WT we have defined copy number changes and loss of heterozygosity in 56 Wilms tumors using high resolution oligonucleotide arrays at a average resolution of ~12 Kb. Consistent deletions were seen on chromosomes 1p, 4q, 7p, 9q, 11p, 11q, 14q, 16q, and 21q. High frequency gains were seen for 1q and lower frequency gains were seen on 7q and chromosomes 8, 12 and 18. The high resolution provided by the SNP mapping arrays has defined minimal regions of deletion for many of these LOH events. Analysis of CNAs by tumor stage show relatively stable karyotypes in stage 1 tumors and more complex aCGH profiles in tumors from stages 3-5.     

Fine mapping of an epilepsy modifier gene on mouse Chromosome 19

Mutations in voltage-gated sodium channels are associated with several types of human epilepsy. Variable expressivity and penetrance are common features of inherited epilepsy caused by sodium channel mutations, suggesting that genetic modifiers may influence clinical severity. The mouse model Scn2a ^Q54 has an epilepsy phenotype due to a mutation in Scn2a that results in elevated persistent sodium current. Phenotype severity in Scn2a ^Q54 mice is dependent on the genetic background. Congenic C57BL/6J.Q54 mice have delayed onset and low seizure frequency compared to (C57BL/6J × SJL/J)F1.Q54 mice. Previously, we identified two modifier loci that influence the Scn2a ^Q54 epilepsy phenotype: Moe1 (modifier of epilepsy 1) on Chromosome 11 and Moe2 on Chromosome 19. We have constructed interval-specific congenic strains to further refine the position of Moe2 on Chromosome 19 to a 5-Mb region. Sequencing and expression analyses of genes in the critical interval suggested two potential modifier candidates: (1) voltage-gated potassium channel subunit subfamily V, member 2 (Kcnv2), and (2) SWI/SNF-related, matrix-associated, actin-dependent regulator of chromatin, subfamily a, member 2 (Smarca2). Based on its biological role in regulating membrane excitability and the association between ion channel variants and seizures, Kcnv2 is a strong functional candidate for Moe2. Modifier genes affecting the epilepsy phenotype of Scn2a ^Q54 mice may contribute to variable expressivity and penetrance in human epilepsy patients with sodium channel mutations.     

Comparative mapping of QTLs for agronomic traits of rice across environments by using a doubled-haploid population

We report here the RFLP mapping of quantitative trait loci (QTLs) which affect some important agronomic traits in cultivated rice. An anther culture-derived doubled-haploid (DH) population was established from a cross between indica and japonica rice varieties. A molecular linkage map comprising 137 markers was constructed based on this population which covered the rice genome at intervals of 14.8 cM on average. The linkage map was used to locate QTLs for such important agronomic traits as heading date, plant height, number of spikelets per panicle, number of grains per panicle, 1 000-grain weight and the percentage of seed set, by interval mapping. Evidence of genotype-by-environment interaction was found by comparing QTL maps of the same population grown in three diverse environments. A total of 22 QTLs for six agronomic traits was detected which were significant in at least one environment, but only seven were significant in all three environments; seven were significant in two environments and eight could only be detected in a single environment. However, QTLs-by-environment interaction was trait dependent. QTLs for spikelets and grains per panicle were common across environments while traits like heading date and plant height were more sensitive to environment. Received: 22 February 1996 / Accepted: 10 May 1996     

Fine mapping of a quantitative trait locus for twinning rate using combined linkage and linkage disequilibrium mapping

A novel and robust method for the fine-scale mapping of genes affecting complex traits, which combines linkage and linkage-disequilibrium information, is proposed. Linkage information refers to recombinations within the marker-genotyped generations and linkage disequilibrium to historical recombinations before genotyping started. The identity-by-descent (IBD) probabilities at the quantitative trait locus (QTL) between first generation haplotypes were obtained from the similarity of the marker alleles surrounding the QTL, whereas IBD probabilities at the QTL between later generation haplotypes were obtained by using the markers to trace the inheritance of the QTL. The variance explained by the QTL is estimated by residual maximum likelihood using the correlation structure defined by the IBD probabilities. Unlinked background genes were accounted for by fitting a polygenic variance component. The method was used to fine map a QTL for twinning rate in cattle, previously mapped on chromosome 5 by linkage analysis. The data consisted of large half-sib families, but the method could also handle more complex pedigrees. The likelihood of the putative QTL was very small along most of the chromosome, except for a sharp likelihood peak in the ninth marker bracket, which positioned the QTL within a region <1 cM in the middle part of bovine chromosome 5. The method was expected to be robust against multiple genes affecting the trait, multiple mutations at the QTL, and relatively low marker density.     

Inferences regarding the numbers and locations of QTLs under multiple-QTL models using interval mapping and composite interval mapping

This paper examines the properties of likelihood maps generated by interval mapping (IM) and composite interval mapping (CIM), two widely used methods for detecting quantitative trait loci (QTLs). We evaluate the usefulness of interpretations of entire maps, rather than only evaluating summary statistics that consider isolated features of maps. A simulation study was performed in which traits with varying genetic architectures, including 20-40 QTLs per chromosome, were examined with both IM and CIM under different marker densities and sample sizes. IM was found to be an unreliable tool for precise estimation of the number and locations of individual QTLs, although it has greater power for simply detecting the presence of QTLs than CIM. The ability of CIM to resolve the correct number of QTLs and to estimate their locations correctly is good if there are three or fewer QTLs per 100 centiMorgans, but can lead to erroneous inferences for more complex architectures. When the underlying genetic architecture of a trait consists of several QTLs with randomly distributed effects and locations likelihood profiles were often indicative of a few underlying genes of large effect. Studies that have detected more than a few QTLs per chromosome should be interpreted with caution.