Epistatic association mapping in homozygous crop cultivars

The genetic dissection of complex traits plays a crucial role in crop breeding. However, genetic analysis and crop breeding have heretofore been performed separately. In this study, we designed a new approach that integrates epistatic association analysis in crop cultivars with breeding by design. First, we proposed an epistatic association mapping (EAM) approach in homozygous crop cultivars. The phenotypic values of complex traits, along with molecular marker information, were used to perform EAM. In our EAM, all the main-effect quantitative trait loci (QTLs), environmental effects, QTL-by-environment interactions and QTL-by-QTL interactions were included in a full model and estimated by empirical Bayes approach. A series of Monte Carlo simulations was performed to confirm the reliability of the new method. Next, the information from all detected QTLs was used to mine novel alleles for each locus and to design elite cross combination. Finally, the new approach was adopted to dissect the genetic basis of seed length in 215 soybean cultivars obtained, by stratified random sampling, from 6 geographic ecotypes in China. As a result, 19 main-effect QTLs and 3 epistatic QTLs were identified, more than 10 novel alleles were mined and 3 elite parental combinations, such as Daqingdou and Zhengzhou790034, were predicted.     

Whole-genome association mapping in elite inbred crop varieties

We have previously shown that linkage disequilibrium (LD) in the elite cultivated barley (Hordeum vulgare) gene pool extends, on average, for <1-5 cM. Based on this information, we have developed a platform for whole genome association studies that comprises a collection of elite lines that we have characterized at 3060 genome-wide single nucleotide polymorphism (SNP) marker loci. Interrogating this data set shows that significant population substructure is present within the elite gene pool and that diversity and LD vary considerably across each of the seven barley chromosomes. However, we also show that a subpopulation comprised of only the two-rowed spring germplasm is less structured and well suited to whole genome association studies without the need for extensive statistical intervention to account for structure. At the current marker density, the two-rowed spring population is suited for fine mapping simple traits that are located outside of the genetic centromeres with a resolution that is sufficient for candidate gene identification by exploiting conservation of synteny with fully sequenced model genomes and the emerging barley physical map.     

Future tools for association mapping in crop plants

Association mapping currently relies on the identification of genetic markers. Several technologies have been adopted for genetic marker analysis, with single nucleotide polymorphisms (SNPs) being the most popular where a reasonable quantity of genome sequence data are available. We describe several tools we have developed for the discovery, annotation, and visualization of molecular markers for association mapping. These include autoSNPdb for SNP discovery from assembled sequence data; TAGdb for the identification of gene specific paired read Illumina GAII data; CMap3D for the comparison of mapped genetic and physical markers; and BAC and Gene Annotator for the online annotation of genes and genomic sequences.     

Family-based association tests for genomewide association scans

With millions of single-nucleotide polymorphisms (SNPs) identified and characterized, genomewide association studies have begun to identify susceptibility genes for complex traits and diseases. These studies involve the characterization and analysis of very-high-resolution SNP genotype data for hundreds or thousands of individuals. We describe a computationally efficient approach to testing association between SNPs and quantitative phenotypes, which can be applied to whole-genome association scans. In addition to observed genotypes, our approach allows estimation of missing genotypes, resulting in substantial increases in power when genotyping resources are limited. We estimate missing genotypes probabilistically using the Lander-Green or Elston-Stewart algorithms and combine high-resolution SNP genotypes for a subset of individuals in each pedigree with sparser marker data for the remaining individuals. We show that power is increased whenever phenotype information for ungenotyped individuals is included in analyses and that high-density genotyping of just three carefully selected individuals in a nuclear family can recover >90% of the information available if every individual were genotyped, for a fraction of the cost and experimental effort. To aid in study design, we evaluate the power of strategies that genotype different subsets of individuals in each pedigree and make recommendations about which individuals should be genotyped at a high density. To illustrate our method, we performed genomewide association analysis for 27 gene-expression phenotypes in 3-generation families (Centre d'Etude du Polymorphisme Humain pedigrees), in which genotypes for ~860,000 SNPs in 90 grandparents and parents are complemented by genotypes for ~6,700 SNPs in a total of 168 individuals. In addition to increasing the evidence of association at 15 previously identified cis-acting associated alleles, our genotype-inference algorithm allowed us to identify associated alleles at 4 cis-acting loci that were missed when analysis was restricted to individuals with the high-density SNP data. Our genotype-inference algorithm and the proposed association tests are implemented in software that is available for free.     

Family-based designs for genome-wide association studies

Association mapping has successfully identified common SNPs associated with many diseases. However, the inability of this class of variation to account for most of the supposed heritability has led to a renewed interest in methods - primarily linkage analysis - to detect rare variants. Family designs allow for control of population stratification, investigations of questions such as parent-of-origin effects and other applications that are imperfectly or not readily addressed in case-control association studies. This article guides readers through the interface between linkage and association analysis, reviews the new methodologies and provides useful guidelines for applications. Just as effective SNP-genotyping tools helped to realize the potential of association studies, next-generation sequencing tools will benefit genetic studies by improving the power of family-based approaches.     

Family-based association studies for next-generation sequencing

An individual's disease risk is determined by the compounded action of both common variants, inherited from remote ancestors, that segregated within the population and rare variants, inherited from recent ancestors, that segregated mainly within pedigrees. Next-generation sequencing (NGS) technologies generate high-dimensional data that allow a nearly complete evaluation of genetic variation. Despite their promise, NGS technologies also suffer from remarkable limitations: high error rates, enrichment of rare variants, and a large proportion of missing values, as well as the fact that most current analytical methods are designed for population-based association studies. To meet the analytical challenges raised by NGS, we propose a general framework for sequence-based association studies that can use various types of family and unrelated-individual data sampled from any population structure and a universal procedure that can transform any population-based association test statistic for use in family-based association tests. We develop family-based functional principal-component analysis (FPCA) with or without smoothing, a generalized T(2), combined multivariate and collapsing (CMC) method, and single-marker association test statistics. Through intensive simulations, we demonstrate that the family-based smoothed FPCA (SFPCA) has the correct type I error rates and much more power to detect association of (1) common variants, (2) rare variants, (3) both common and rare variants, and (4) variants with opposite directions of effect from other population-based or family-based association analysis methods. The proposed statistics are applied to two data sets with pedigree structures. The results show that the smoothed FPCA has a much smaller p value than other statistics.     

Family-based association analysis of theMAPT gene in Parkinson

The MAPT gene has been shown to be associated with several neurodegenerative disorders, including forms of parkinsonism and Parkinson disease (PD), but the results reveal population differences. We investigated the association of 10 single-nucleotide polymorphisms (SNPs) in the region ofMAPT on chromosome 17q21 with PD and age at onset, by using 443 discordant sib pairs in PD from a public dataset (Mayo-Perlegen LEAPS Collaboration). Association with PD was assessed by the FBAT using generalized estimating equations (FBAT-GEE), while the association with age at onset as a quantitative trait was evaluated using the FBAT-logrank statistic. Five SNPs were significantly associated with PD (P < 0.05) in an additive model, and 9 SNPs were associated with PD (P < 0.05) in dominant and recessive models. Interestingly, 8 PD-associated SNPs were also associated with age at onset of PD (P < 0.05) in dominant and recessive models. The SNP most significantly associated with PD and age at onset was rs17649641 (P = 0.015 and 0.021, respectively). Two-SNP haplotypes inferred from rs17563965 and rs17649641 also showed association with PD (P = 0.018) and age at onset (P = 0.026). These results provide further support for the role of MAPT in development of PD.     

Family-based association analysis with tightly linked markers

Refining genomic regions which have been identified by linkage analysis to contain a disease susceptibility locus has proven to be a challenging task. Detecting association between the disease and a genetic marker can significantly narrow down the candidate region. Since an adequate sample of families is already available from the genome scan, family-based association tests may be used to search for association. The use of haplotypes consisting of tightly linked markers can be more powerful for detecting association than the use of individual markers. An extension of the transmission/disequilibrium test to allow the simultaneous analysis of more than one marker locus is complicated by ambiguity of phase in some families of the sample. The present paper shows that a recently proposed method for the analysis of nuclear families with a single affected child can be viewed as a special application of a more general principle. This observation justifies several modifications, potentially increasing the power, as well as an extension of the method to allow the analysis of general nuclear families. Finally, the problem of missing parental genotypes is discussed.     

Family-based tests of association in the presence of linkage

Linkage analysis may not provide the necessary resolution for identification of the genes underlying phenotypic variation. This is especially true for gene-mapping studies that focus on complex diseases that do not exhibit Mendelian inheritance patterns. One positional genomic strategy involves application of association methodology to areas of identified linkage. Detection of association in the presence of linkage localizes the gene(s) of interest to more-refined regions in the genome than is possible through linkage analysis alone. This strategy introduces a statistical complexity when family-based association tests are used: the marker genotypes among siblings are correlated in linked regions. Ignoring this correlation will compromise the size of the statistical hypothesis test, thus clouding the interpretation of test results. We present a method for computing the expectation of a wide range of association test statistics under the null hypothesis that there is linkage but no association. To standardize the test statistic, an empirical variance-covariance estimator that is robust to the sibling marker-genotype correlation is used. This method is widely applicable: any type of phenotypic measure or family configuration can be used. For example, we analyze a deletion in the A2M gene at the 5' splice site of "exon II" of the bait region in Alzheimer disease (AD) discordant sibships. Since the A2M gene lies in a chromosomal region (chromosome 12p) that consistently has been linked to AD, association tests should be conducted under the null hypothesis that there is linkage but no association.     

Family-based association tests using genotype data with uncertainty

Family-based association studies have been widely used to identify association between diseases and genetic markers. It is known that genotyping uncertainty is inherent in both directly genotyped or sequenced DNA variations and imputed data in silico. The uncertainty can lead to genotyping errors and missingness and can negatively impact the power and Type I error rates of family-based association studies even if the uncertainty is independent of disease status. Compared with studies using unrelated subjects, there are very few methods that address the issue of genotyping uncertainty for family-based designs. The limited attempts have mostly been made to correct the bias caused by genotyping errors. Without properly addressing the issue, the conventional testing strategy, i.e. family-based association tests using called genotypes, can yield invalid statistical inferences. Here, we propose a new test to address the challenges in analyzing case-parents data by using calls with high accuracy and modeling genotype-specific call rates. Our simulations show that compared with the conventional strategy and an alternative test, our new test has an improved performance in the presence of substantial uncertainty and has a similar performance when the uncertainty level is low. We also demonstrate the advantages of our new method by applying it to imputed markers from a genome-wide case-parents association study.     

Family-based association study of synapsin II and schizophrenia

Synapsin II has been proposed as a candidate gene for vulnerability to schizophrenia on the basis of its function and its location in a region of the genome implicated by linkage studies in families with schizophrenia. We recently reported positive association of synapsin II with schizophrenia in a case-control study (Chen et al. 2004). However, since case-control analyses can generate false-positive results in the presence of minor degrees of population stratification, we have performed a replication study in 366 additional Han Chinese probands and their parents by use of analyses of transmission/disequilibrium for three in/del markers and three single-nucleotide polymorphisms. Positive association was observed for rs2307981 (P =.02), rs2308169 (P =.005), rs308963 (P =.002), rs795009 (P =.02), and rs2307973 (P =.02). For transmission of six-marker haplotypes, the global P value was.0000016 (5 degrees of freedom), principally because of overtransmission of the most common haplotype, CAA/-/G/T/C/- (frequency 53.6%; chi (2) = 20.8; P =.0000051). This confirms our previous study and provides further support for the role of synapsin II variants in susceptibility to schizophrenia.     

Phenotypic diversity and association mapping for fruit quality traits in cultivated tomato and related species

Association mapping has been proposed as an efficient approach to assist in the identification of the molecular basis of agronomical traits in plants. For this purpose, we analyzed the phenotypic and genetic diversity of a large collection of tomato accessions including 44 heirloom and vintage cultivars (Solanum lycopersicum), 127 S. lycopersicum var. cerasiforme (cherry tomato) and 17 Solanum pimpinellifolium accessions. The accessions were genotyped using a SNPlex? assay of 192 SNPs, among which 121 were informative for subsequent analysis. Linkage disequilibrium (LD) of pairwise loci and population structure were analyzed, and the association analysis between SNP genotypes and ten fruit quality traits was performed using a mixed linear model. High level of LD was found in the collection at the whole genome level. It was lower when considering only the 127 S. lycopersicum var. cerasiforme accessions. Genetic structure analysis showed that the population was structured into two main groups, corresponding to cultivated and wild types and many intermediates. The number of associations detected per trait varied, according to the way the structure was taken into account, with 0–41 associations detected per trait in the whole collection and a maximum of four associations in the S. lycopersicum var. cerasiforme accessions. A total of 40 associations (30 %) were co-localized with previously identified quantitative trait loci. This study thus showed the potential and limits of using association mapping in tomato populations.     

Molecular mapping and tagging of genes in crop plants

In India, molecular mapping and tagging of agronomically important genes using RFLP and RAPD markers have been carried out in three different crops: rice, mustard and chickpea. In rice, tagging of genes for resistance to gall midge and blast has been accomplished. Molecular mapping of cooking quality traits in rice is in progress. For fingerpringting rice cultivars, suitable probe enzyme combinations have been identified. In mustard, a partial RFLP linkage map has been constructed and one of the yellow seed-coat colour loci has been mapped. Significant associations of RFLP markers with quantitative traits have also been established. Potential use of RAPD markers to identify heterotic groups among mustard accessions has been demonstrated. In chickpea, the occurrence of considerable interspecific DNA polymorphism as revealed by RAPD analysis has facilitated construction of a partial linkage map.     

Family-based association of a low producing lymphotoxin-alpha allele with reduced Plasmodium falciparum parasitemia

Tumor necrosis factor (TNF)-related genes are thought to play a role in human malaria. TNF polymorphisms have been associated with severe malaria, mild malaria, and parasitemia. Lymphotoxin-alpha gene (LTA) that belongs to the TNF family is one such candidate gene. Here we report the family-based association analysis of a cis-regulatory lymphotoxin-alpha polymorphism with parasitemia in two independent populations living in Burkina Faso. Analysis of 199 subjects (34 families) living in an urban endemic area revealed the association of the low producing LTA+80A allele with reduced parasitemia. Furthermore, there was evidence of significant LTA+80-by-age and LTA+80-by-gender interactions. In another set of 318 residents (55 families) in a rural endemic area, we found both the association of the low producing LTA+80A allele with reduced parasitemia and LTA+80-by-age and LTA+80-by-gender interactions. This study suggests that LTA+80 polymorphism influences parasitemia and acts in an age- and gender-dependent manner.     

作物抗旱相关性状的QTLs定位研究进展

提高作物品种的抗旱性、获得高产稳产是抗旱育种的最终目标。作物分子连锁图谱的构建及其它分子遗传学研究进展为改良作物抗旱性提供了新机遇。Ｔａｎｋｓｌｅｙ等[1]指出,通过ＲＦＬＰ或其他分子标记进行标记辅助选择,为难以测量的性状提供了一条重要的选择途径。通过对抗旱相关性状的数量性状位点(ＱＴＬｓ)的标记,就可以把复杂的性状作为一套单基因性状进行分析和选择。一旦找到紧密连锁的标记(1-5ｃＭ),就可以在育种工作中进行标记辅助选择[2]。分子标记使育种家无需测定表型就能够追踪调控抗旱性状的遗传位点,可免去多年多点的大量田间…     

Different behaviour of crop species in phosphate absorption

Summary Isotopic-dilution technique was used to study the differential phosphate absorption abilities of several field crops. The response of crops was found to be inversely related to the ratio of phosphorus absorbed from the soil to that absorbed from the fertilizer. The ‘A’ values ranged from 2.03 ppm for mustard to 21.77 ppm for soybeans. A highly significant correlation (r=0.77**) was found between per cent yields and the ‘A’ values.     

Pedigree assessment using RAPD-DGGE in cereal crop species

Summary The introduction of molecular biology methodologies to plant improvement programs offers an invaluable opportunity for extensive germplasm characterization. However, the detection of adequate DNA polymorphism in self-pollinating species remains on obstacle. We have optimized a denaturing-gradient-gel electrophoresis (DGGE) system which, when used in combination with random amplified polymorphic DNA (RAPD) analysis, greatly facilitates the detection of reproducible DNA polymorphism among closely related plant lines. We have used this approach to estimate pedigree relationships among a spectrum of plant materials in wheat, barley and oat. Based on analysis with one or two primers, we were able to distinguish soft from hard winter wheat, and 2-rowed from 6-rowed barley. Further analysis with additional primers allowed resolution of polymorpisms even among closely related lines in highly selected populations. We placed 17 cultivars of oat into two distinct clusters that differed significantly from previous oat pedigree assessments. We believe that DGGE-RAPD is a superior method for detecting DNA polymorphism when compared to RFLP, agarose-RAPD, or polyacrylamide-RAPD methods.     

Family-based genome-wide association study of frontal theta oscillations identifies potassium channel gene KCNJ6

Event-related oscillations (EROs) represent highly heritable neuroelectric correlates of cognitive processes that manifest deficits in alcoholics and in offspring at high risk to develop alcoholism. Theta ERO to targets in the visual oddball task has been shown to be an endophenotype for alcoholism. A family-based genome-wide association study was performed for the frontal theta ERO phenotype using 634 583 autosomal single nucleotide polymorphisms (SNPs) genotyped in 1560 family members from 117 families densely affected by alcohol use disorders, recruited in the Collaborative Study on the Genetics of Alcoholism. Genome-wide significant association was found with several SNPs on chromosome 21 in KCNJ6 (a potassium inward rectifier channel; KIR3.2/GIRK2), with the most significant SNP at P = 4.7 × 10(-10)). The same SNPs were also associated with EROs from central and parietal electrodes, but with less significance, suggesting that the association is frontally focused. One imputed synonymous SNP in exon four, highly correlated with our top three SNPs, was significantly associated with the frontal theta ERO phenotype. These results suggest KCNJ6 or its product GIRK2 account for some of the variations in frontal theta band oscillations. GIRK2 receptor activation contributes to slow inhibitory postsynaptic potentials that modulate neuronal excitability, and therefore influence neuronal networks.