Importance of epistasis as the genetic basis of heterosis in an elite rice hybrid

The genetic basis of heterosis was investigated in an elite rice hybrid by using a molecular linkage map with 150 segregating loci covering the entire rice genome. Data for yield and three traits that were components of yield were collected over 2 years from replicated field trials of 250 F2:3 families. Genotypic variations explained from about 50% to more than 80% of the total variation. Interactions between genotypes and years were small compared with the main effects. A total of 32 quantitative trait loci (QTLs) were detected for the four traits; 12 were observed in both years and the remaining 20 were detected in only one year. Overdominance was observed for most of the QTLs for yield and also for a few QTLs for the component traits. Correlations between marker heterozygosity and trait expression were low, indicating that the overall heterozygosity made little contribution to heterosis. Digenic interactions, including additive by additive, additive by dominance, and dominance by dominance, were frequent and widespread in this population. The interactions involved large numbers of marker loci, most of which individually were not detectable on single-locus basis; many interactions among loci were detected in both years. The results provide strong evidence that epistasis plays a major role as the genetic basis of heterosis.

Evolution of genome–phenome diversity under environmental stress

The genomic era revolutionized evolutionary biology. The enigma of genotypic-phenotypic diversity and biodiversity evolution of genes, genomes, phenomes, and biomes, reviewed here, was central in the research program of the Institute of Evolution, University of Haifa, since 1975. We explored the following questions. (i) How much of the genomic and phenomic diversity in nature is adaptive and processed by natural selection? (ii) What is the origin and evolution of adaptation and speciation processes under spatiotemporal variables and stressful macrogeographic and microgeographic environments? We advanced ecological genetics into ecological genomics and analyzed globally ecological, demographic, and life history variables in 1,200 diverse species across life, thousands of populations, and tens of thousands of individuals tested mostly for allozyme and partly for DNA diversity. Likewise, we tested thermal, chemical, climatic, and biotic stresses in several model organisms. Recently, we introduced genetic maps and quantitative trait loci to elucidate the genetic basis of adaptation and speciation. The genome–phenome holistic model was deciphered by the global regressive, progressive, and convergent evolution of subterranean mammals. Our results indicate abundant genotypic and phenotypic diversity in nature. The organization and evolution of molecular and organismal diversity in nature at global, regional, and local scales are nonrandom and structured; display regularities across life; and are positively correlated with, and partly predictable by, abiotic and biotic environmental heterogeneity and stress. Biodiversity evolution, even in small isolated populations, is primarily driven by natural selection, including diversifying, balancing, cyclical, and purifying selective regimes, interacting with, but ultimately overriding, the effects of mutation, migration, and stochasticity.

A rat genetic map constructed by representational difference analysis markers with suitability for large-scale typing.

Representational difference analysis (RDA) was applied to isolate chromosomal markers in the rat. Four series of RDA [restriction enzymes, BamHI and HindIII; subtraction of ACI/N (ACI) amplicon from BUF/Nac (BUF) amplicon and vice versa] yielded 131 polymorphic markers; 125 of these markers were mapped to all chromosomes except for chromosome X. This was done by using a mapping panel of 105 ACI x BUF F2 rats. To complement the relative paucity of chromosomal markers in the rat, genetically directed RDA, which allows isolation of polymorphic markers in the specific chromosomal region, was performed. By changing the F2 driver-DNA allele frequency around the region, four markers were isolated from the D1Ncc1 locus. Twenty-five of 27 RDA markers were informative regarding the dot blot analysis of amplicons, hybridizing only with tester amplicons. Dot blot analysis at a high density per unit of area made it possible to process a large number of samples. Quantitative trait loci can now be mapped in the rat genome by processing a large number of samples with RDA markers and then by isolating markers close to the loci of interest by genetically directed RDA.

The weediness of wild plants: molecular analysis of genes influencing dispersal and persistence of johnsongrass, Sorghum halepense (L.) Pers.

Many major weeds rely upon vegetative dispersal by rhizomes and seed dispersal by "shattering" of the mature inflorescence. We report molecular analysis of these traits in a cross between cultivated and wild species of Sorghum that are the probable progenitors of the major weed "johnsongrass." By restriction fragment length polymorphism mapping, variation in the number of rhizomes producing above-ground shoots was associated with three quantitative trait loci (QTLs). Variation in regrowth (ratooning) after overwintering was associated with QTLs accounting for additional rhizomatous growth and with QTLs influencing tillering. Vegetative buds that become rhizomes are similar to those that become tillers--one QTL appears to influence the number of such vegetative buds available, and additional independent genes determine whether individual buds differentiate into tillers or rhizomes. DNA markers described herein facilitate cloning of genes associated with weediness, comparative study of rhizomatousness in other Poaceae, and assessment of gene flow between cultivated and weedy sorghums--a risk that constrains improvement of sorghum through biotechnology. Cloning of "weediness" genes may create opportunities for plant growth regulation, in suppressing propagation of weeds and enhancing productivity of major forage, turf, and "ratoon" crops.

Cosegregation analysis of natriuretic peptide genes and blood pressure in the spontaneously hypertensive rat

1. The natriuretic peptide precursor A (Nppa) and B (Nppb) genes are candidate genes for hypertension and cardiac hypertrophy in the spontaneously hypertensive rat (SHR). The purpose of the present study was to determine the role of the Nppa and Nppb genes in the development of hypertension in the SHR. 2. A cohort (n = 162) of F2 segregating intercross animals was established between strains of hypertensive SHR and normotensive Wistar-Kyoto rats. Blood pressure and heart weight were measured in each rat at 12-16 weeks of age. Rats were genotyped using 11 informative microsatellite markers, distributed in the vicinity of the Nppa marker on rat chromosome 5 including an Nppb marker. The phenotype values were compared with genotype using the computer package MAP-MAKER 3.0 (Whitehead Institute, Boston, MA, USA) to determine whether there was a link between the genetic variants of the natriuretic peptide family and blood pressure or cardiac hypertrophy. 3. A strong correlation was observed between the Nppa marker and blood pressure. A quantitative trait locus (QTL) for blood pressure on chromosome 5 was identified between the Nppa locus and the D5Mgh15 marker, less than 2 cM from the Nppa locus. The linkage score for the blood pressure QTL on chromosome 5 was 3.8 and the QTL accounted for 43% of the total variance of systolic blood pressure, 54% of diastolic blood pressure and 59% of mean blood pressure. No association was found between the Nppb gene and blood pressure. This is the first report of linkage between the Nppa marker and blood pressure in the rat. There was no correlation between the Nppa or Nppb genes or other markers in this region and either heart weight or left ventricular weight in F2 rats. 4. These findings suggest the existence of a blood pressure-dependent Nppa marker variant or a gene close to Nppa predisposing to spontaneous hypertension in the rat. It provides a strong foundation for further detailed genetic studies in congenic strains, which may help to narrow down the location of this gene and lead to positional cloning.

Multivariate QTL linkage analysis suggests a QTL for platelet count on chromosome 19q

Platelet count is a highly heritable trait with genetic factors responsible for around 80% of the phenotypic variance. We measured platelet count longitudinally in 327 monozygotic and 418 dizygotic twin pairs at 12, 14 and 16 years of age. We also performed a genome-wide linkage scan of these twins and their families in an attempt to localize QTLs that influenced variation in platelet concentrations. Suggestive linkage was observed on chromosome 19q13.13-19q13.31 at 12 (LOD=2.12, P=0.0009), 14 (LOD=2.23, P=0.0007) and 16 (LOD=1.01, P=0.016) years of age and multivariate analysis of counts at all three ages increased the LOD to 2.59 (P=0.0003). A possible candidate in this region is the gene for glycoprotein VI, a receptor involved in platelet aggregation. Smaller linkage peaks were also seen at 2p, 5p, 5q, 10p and 15q. There was little evidence for linkage to the chromosomal regions containing the genes for thrombopoietin (3q27) and the thrombopoietin receptor (1q34), suggesting that polymorphisms in these genes do not contribute substantially to variation in platelet count between healthy individuals.

Copulas in QTL mapping

The standard variance components method for mapping quantitative trait loci is derived on the assumption of normality. Unsurprisingly, statistical tests based on this method do not perform so well if this assumption is not satisfied. We use the statistical concept of copulas to relax the assumption of normality and derive a test that can perform well under any distribution of the continuous trait. In particular, we discuss bivariate normal copulas in the context of sib-pair studies. Our approach is illustrated by a linkage analysis of lipoprotein(a) levels, whose distribution is highly skewed. We demonstrate that the asymptotic critical levels of the test can still be calculated using the interval mapping approach. The new method can be extended to more general pedigrees and multivariate phenotypes in a similar way as the original variance components method.

Comparison of identity by descent and identity by state for detecting genetic regions under selection in a sorghum pedigree breeding program

Seventy sorghum inbred lines which formed part of the Queensland Department of Primary Industries (QDPI) sorghum breeding program were screened with 104 previously mapped RFLP markers. The lines were related by pedigree and consisted of ancestral source lines, intermediate lines and recent releases from the program. We compared the effect of defining marker alleles using either identity by state (IBS) or identity by descent (IBD) on our capacity to trace markers through the pedigree and detect evidence of selection for particular alleles. Allelic identities defined using IBD were much more sensitive for detecting non-Mendelian segregation in this pedigree. Only one marker allele showed significant evidence of selection when IBS was used compared with ten regions with particular allelic identities when IBD was used. Regions under selection were compared with the location of QTLs for agronomic traits known to be under selection in the breeding program. Only two of the ten regions were associated with known QTLs that matched with knowledge of the agronomic characteristics of the ancestral lines. Some of the other regions were hypothesised to be associated with genes for particular traits based on the properties of the ancestral source lines.

On systems thinking, systems biology and the in Silico Plant

The recent summary report of a Department of Energy Workshop on Plant Systems Biology (P.V. Minorsky [2003] Plant Physiol 132: 404-409) offered a welcomed advocacy for systems analysis as essential in understanding plant development, growth, and production. The goal of the Workshop was to consider methods for relating the results of molecular research to real-world challenges in plant production for increased food supplies, alternative energy sources, and environmental improvement. The rather surprising feature of this report, however, was that the Workshop largely overlooked the rich history of plant systems analysis extending over nearly 40 years (Sinclair and Seligman, 1996) that has considered exactly those challenges targeted by the Workshop. Past systems research has explored and incorporated biochemical and physiological knowledge into plant simulation models from a number of perspectives. The research has resulted in considerable understanding and insight about how to simulate plant systems and the relative contribution of various factors in influencing plant production. These past activities have contributed directly to research focused on solving the problems of increasing biomass production and crop yields. These modeling approaches are also now providing an avenue to enhance integration of molecular genetic technologies in plant improvement (Hammer et al., 2002).

A genetic linkage map in autotetraploid lucerne adapted to northern Australia, and use of the map to identify DNA markers linked to resistance to Phytophthora medicaginis

Phytophthora root rot, caused by Phytophthora medicaginis, is a major limitation to lucerne ( Medicago sativa L.) production in Australia and North America. Quantitative trait loci (QTLs) involved in resistance to P. medicaginis were identified in a lucerne backcross population of 120 individuals. A genetic linkage map was constructed for tetraploid lucerne using 50 RAPD ( randomly amplified polymorphic DNA), 104 AFLP (amplified fragment length polymorphism) markers, and one SSR ( simple sequence repeat or microsatellite) marker, which originated from the resistant parent (W116); 13 markers remain unlinked. The linkage map contains 18 linkage groups covering 2136.5 cM, with an average distance of 15.0 cM between markers. Four of the linkage groups contained only either 2 or 3 markers. Using duplex markers and repulsion phase linkages the map condensed to 7 homology groups and 2 unassigned linkage groups. Three regions located on linkage groups 2, 14, and 18, were identified as associated with root reaction and the QTLs explained 6 - 15% of the phenotypic variation. The research also indicates that different resistance QTLs are involved in conferring resistance in different organs. Two QTLs were identified as associated with disease resistance expressed after inoculation of detached leaves. The marker, W11-2 on group 18, identified as associated with root reaction, contributed 7% of the phenotypic variation in leaf response in our population. This marker appears to be linked to a QTL encoding a resistance factor contributing to both root and leaf reaction. One other QTL, not identified as associated with root reaction, was positioned on group 1 and contributed to 6% of the variation. This genetic linkage map provides an entry point for future molecular-based improvement of lucerne in Australia, and markers linked to the QTLs we have reported should be useful for marker-assisted selection for partial resistance to P. medicaginis in lucerne.

The potential of microarrays to assist shrimp breeding and production: a review

The shrimp aquaculture industry is a relatively new livestock industry, having developed over the past 30 years. Thus, it is poised to take advantage of new technologies from the outset of selective breeding programs. This contrasts with long established livestock industries, where there are already highly specialised breeds. This review focuses specifically on the potential application of microarrays to shrimp breeding. Potential applications of microarrays in selective breeding programs are summarised. Microarrays can be used as a rapid means to generate molecular markers for genetic linkage mapping, and genetic maps have been constructed for yeast, Arabidopsis and barley using microarray technology. Microarrays can also be used in the hunt for candidate genes affecting particular traits, leading to development of perfect markers for these traits (i.e. causative mutations). However, this requires that microarray analysis be combined with genetic linkage mapping, and that substantial genomic information is available for the species in question. A novel application of microarrays is to treat gene expression as a quantitative trait in itself and to combine this with linkage mapping to identify quantitative trait loci controlling the levels of gene expression; this approach may identify higher level regulatory genes in specific pathways. Finally, patterns of gene expression observed using microarrays may themselves be treated as phenotypic traits in selection programs (e.g. a particular pattern of gene expression might be indicative of a disease tolerant individual). Microarrays are now being developed for a number of shrimp species in laboratories around the world, primarily with a focus on identifying genes involved in the immune response. However, at present, there is no central repository of shrimp genomic information, which limits the rate at which shrimp genomic research can be progressed. The application of microarrays to shrimp breeding will be extremely limited until there is a shared repository of genomic information for shrimp, and the collective will and resources to develop comprehensive genomic tools for shrimp.

Relationships between hard-seededness and seed weight in mungbean (Vigna radiata) assessed by QTL analysis

Weather damage reduces the value of commercial mungbean, but hard-seededness can reduce the level of damage. However, attempts to breed large- and hard-seeded mungbean varieties have been unsuccessful. To understand the relationship between seed weight and hard-seededness, these traits were investigated using a quantitative trait loci (QTL) mapping approach with a recombinant inbred population derived from a cross between a completely soft-seeded variety and a completely hard-seeded genotype. The two parental genotypes also had a sixfold difference in seed weight. QTL analyses revealed four loci for hard-seededness and I I loci for seed weight. Two of the hardseededness loci co-localized with seed weight QTL. When seed weight was used as a covariate in the analysis of hard-seededness from the field data, two of the four hard-seeded QTL remained significant with the effect at one of these remaining unchanged. These results explain why retaining hard-seededness in large seeded mungbean lines has been unsuccessful. The existence of a persistent locus, however, indicated that breeding large and persistently hard-seeded varieties of mungbean may be possible.

Assumption-free estimation of heritability from genome-wide identity-by-descent sharing between full siblings

The study of continuously varying, quantitative traits is important in evolutionary biology, agriculture, and medicine. Variation in such traits is attributable to many, possibly interacting, genes whose expression may be sensitive to the environment, which makes their dissection into underlying causative factors difficult. An important population parameter for quantitative traits is heritability, the proportion of total variance that is due to genetic factors. Response to artificial and natural selection and the degree of resemblance between relatives are all a function of this parameter. Following the classic paper by R. A. Fisher in 1918, the estimation of additive and dominance genetic variance and heritability in populations is based upon the expected proportion of genes shared between different types of relatives, and explicit, often controversial and untestable models of genetic and non-genetic causes of family resemblance. With genome-wide coverage of genetic markers it is now possible to estimate such parameters solely within families using the actual degree of identity-by-descent sharing between relatives. Using genome scans on 4,401 quasi-independent sib pairs of which 3,375 pairs had phenotypes, we estimated the heritability of height from empirical genome-wide identity-by-descent sharing, which varied from 0.374 to 0.617 (mean 0.498, standard deviation 0.036). The variance in identity-by-descent sharing per chromosome and per genome was consistent with theory. The maximum likelihood estimate of the heritability for height was 0.80 with no evidence for non-genetic causes of sib resemblance, consistent with results from independent twin and family studies but using an entirely separate source of information. Our application shows that it is feasible to estimate genetic variance solely from within- family segregation and provides an independent validation of previously untestable assumptions. Given sufficient data, our new paradigm will allow the estimation of genetic variation for disease susceptibility and quantitative traits that is free from confounding with non-genetic factors and will allow partitioning of genetic variation into additive and non-additive components.

A linkage study of academic skills defined by the Queensland Core Skills Test

This study used genome-wide linkage analysis to detect Quantitative Trait Loci (QTLs) implicated in variation in general academic achievement as measured by the Queensland Core Skills Test (QCST) (Queensland Studies Authority, 2004). Data from 210 families were analysed. While no empirically derived significant or suggestive peaks for general academic achievement were indicated a peak on chromosome 2 was observed in a region where Posthuma et al. (2005) reported significant linkage for Performance IQ (PIQ) and suggestive linkage for Full Scale IQ (FSIQ), and Luciano et al. (this issue) observed significant linkage for PIQ and word reading. A peak on chromosome 18 was also observed approximately 20 cM removed from a region recently implicated in reading achievement. In addition, on chromosomes 2 and 18 peaks for a number of specific academic skills, two of which were suggestive, coincided with the general academic achievement peaks. The findings suggest that variation in general academic achievement is influenced by genes on chromosome 2 which have broad influence on a variety of cognitive abilities.

Analysing diversity in sugarcane resistance gene analogues

As resistance genes have been shown to contain conserved motifs and cluster in many plant genomes, the identification of resistance gene analogues can be used as a strategy for both the discovery of DNA markers linked to disease resistance loci and the map-based cloning of disease resistance genes. Sugarcane suffers from many important diseases and an analysis of resistance gene analogues offers a means to identify DNA markers linked to resistance loci. However, sugarcane has the most complex genome of any crop plant and initially it is important to understand the extent of resistance gene analogue diversity in the sugarcane genome before genetic analysis. We review herein how more than 100 expressed sequence tags with homology to different resistance genes have been identified in sugarcane with many mapped as single-dose restriction fragment length polymorphism markers. Importantly, some of these resistance gene analogues have been shown to be linked to disease resistance genes or disease quantitative trait loci. In an attempt to more efficiently analyse additional resistance gene analogues in sugarcane, we report on experiments aimed at investigating the molecular diversity of several resistance gene analogue families using a modified form of a technique termed Ecotilling. Using Ecotilling, we were able to rapidly detect single nucleotide polymorphisms in fragments amplified by PCR from four different resistance gene analogue families, SoRP1D, SoPTO, SoXa21 and SoHs1pro-1. An analysis of a diverse set of sugarcane varieties, including modern sugarcane cultivars and several S. officinarum and S. spontaneum clones, indicated that all amplicons, apart from SoHs1pro-1, contained significant polymorphism within the gene region studied. However, a comparison among these sugarcane clones, including between the parents of two sugarcane mapping populations, indicated that most polymorphisms were multi-dose, not single-dose, preventing their genetic map location or association with disease susceptibility or resistance from being determined.