Estabilidade de QTLs ligados à resistência dos citros a gomose, causada por Phytophthora parasitica

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Variabilidade genética e identificação de QTLs de tíbia e peso corporal em Gallus gallus

Pós-graduação em Genética e Melhoramento Animal - FCAV

High-resolution mapping and isolation of a yeast artificial chromosome contig containing fw2.2: A major fruit weight quantitative trait locus in tomato

A high-resolution physical and genetic map of a major fruit weight quantitative trait locus (QTL), fw2.2, has been constructed for a region of tomato chromosome 2. Using an F2 nearly isogenic line mapping population (3472 individuals) derived from Lycopersicon esculentum (domesticated tomato) × Lycopersicon pennellii (wild tomato), fw2.2 has been placed near TG91 and TG167, which have an interval distance of 0.13 ± 0.03 centimorgan. The physical distance between TG91 and TG167 was estimated to be ≤ 150 kb by pulsed-field gel electrophoresis of tomato DNA. A physical contig composed of six yeast artificial chromosomes (YACs) and encompassing fw2.2 was isolated. No rearrangements or chimerisms were detected within the YAC contig based on restriction fragment length polymorphism analysis using YAC-end sequences and anchored molecular markers from the high-resolution map. Based on genetic recombination events, fw2.2 could be narrowed down to a region less than 150 kb between molecular markers TG91 and HSF24 and included within two YACs: YAC264 (210 kb) and YAC355 (300 kb). This marks the first time, to our knowledge, that a QTL has been mapped with such precision and delimited to a segment of cloned DNA. The fact that the phenotypic effect of the fw2.2 QTL can be mapped to a small interval suggests that the action of this QTL is likely due to a single gene. The development of the high-resolution genetic map, in combination with the physical YAC contig, suggests that the gene responsible for this QTL and other QTLs in plants can be isolated using a positional cloning strategy. The cloning of fw2.2 will likely lead to a better understanding of the molecular biology of fruit development and to the genetic engineering of fruit size characteristics.

Dissection of a quantitative trait locus for genetic hypertension on rat chromosome 10.

We have previously identified a locus on rat chromosome 10 as carrying a major hypertension gene, BP/SP-1. The 100:1 odds support interval for this gene extended over a 35-centimorgan (cM) region of the chromosome that included the angiotensin I-converting enzyme (ACE) locus as demonstrated in a cross between the stroke-prone spontaneously hypertensive rat (SHRSPHD) and the normotensive Wistar-Kyoto (WKY-0HD) rat. Here we report on the further characterization of BP/SP-1, using a congenic strain, WKY-1HD. WKY-1HD animals carry a 6-cM chromosomal fragment genotypically identical with SHRSPHD on chromosome 10, 26 cM away from the ACE locus. Higher blood pressures in the WKY-1HD strain compared with the WKY-0HD strain, as well as absence of linkage of the chromosome 10 region to blood pressure in an F2 (WKY-1HD x SHRSPHD) population suggested the existence of a quantitative trait locus, termed BP/SP-1a, that lies within the SHRSP-congenic region in WKY-1HD. Linkage analysis in the F2 (WKY-0HD x SHRSPHD) cross revealed that BP/SP-1a is linked to basal blood pressure, whereas a second locus on chromosome 10, termed BP/SP-1b, that maps closer to the ACE locus cosegregates predominantly with blood pressure after exposure to excess dietary NaCl. Thus, we hypothesize that the previously reported effect of BP/SP-1 represents a composite phenotype that can be dissected into at least two specific components on the basis of linkage data and congenic experimentation. One of the loci identified, BP/SP-1a, represents the most precisely mapped locus affecting blood pressure that has so far been characterized by random-marker genome screening.

A major quantitative trait locus for CD4-CD8 ratio is located on chromosome 11

CD4-CD8 ratio is an important diagnostic measure of immune system functioning. In particular, CD4-CD8 ratio predicts the time taken for progression of HIV infection to acquired immune deficiency syndrome (AIDS) and the long-term survival of AIDS patients. To map genes that regulate differences between healthy individuals in CD4-CD8 ratio, we typed 757 highly polymorphic microsatellite markers at an average spacing of similar to5 cM across the genome in 405 pairs of dizygotic twins at ages 12, 14 and 16. We used multipoint variance components linkage analysis to test for linkage between marker loci and CD4-CD8 ratio at each age. We found suggestive evidence of linkage on chromosome 11p in 12-year-old twins (LOD=2.55, P=0.00031) and even stronger evidence of linkage in the same region at age 14 (LOD 3.51, P=0.00003). Possible candidate genes include CD5 and CD6, which encode cell membrane proteins involved in the positive selection of thymocytes. We also found suggestive evidence of linkage at other areas of the genome including regions on chromosomes 1, 3, 4, 5, 6, 12, 13, 15, 17 and 22.

QTLs mapping for primary metabolites responsible of the organoleptic and nutritional characteristics of strawberry (Fragaria x ananassa)

The cultivated strawberry (Fragaria x ananassa) is the berry fruit most consumed worldwide and is well-known for its delicate flavour and nutritional properties. However, fruit quality attributes have been lost or reduced after years of traditional breeding focusing mainly on agronomical traits. To face the obstacles encountered in the improvement of cultivated crops, new technological tools, such as genomics and high throughput metabolomics, are becoming essential for the identification of genetic factors responsible of organoleptic and nutritive traits. Integration of “omics” data will allow a better understanding of the molecular and genetic mechanisms underlying the accumulation of metabolites involved in the flavour and nutritional value of the fruit. To identify genetic components affecting/controlling? fruit metabolic composition, here we present a quantitative trait loci (QTL) analysis using a 95 F1 segregating population derived from genotypes ‘1392’, selected for its superior flavour, and ‘232’ selected based in high yield (Zorrilla-Fontanesi et al., 2011; Zorrilla-Fontanesi et al., 2012). Metabolite profiling was performed on red stage strawberry fruits using gas chromatography hyphenated to time-of-flight mass spectrometry, which is a rapid and highly sensitive approach, allowing a good coverage of the central pathways of primary metabolism. Around 50 primary metabolites, including sugars, sugars derivatives, amino and organic acids, were detected and quantified after analysis in each individual of the population. QTL mapping was performed on the ‘232’ x ‘1392’ population separately over two successive years, based on the integrated linkage map (Sánchez-Sevilla et al., 2015). First, significant associations between metabolite content and molecular markers were identified by the non-parametric test of Kruskal-Wallis. Then, interval mapping (IM), as well as the multiple QTL method (MQM) allowed the identification of QTLs in octoploid strawberry. A permutation test established LOD thresholds for each metabolite and year. A total of 132 QTLs were detected in all the linkage groups over the two years for 42 metabolites out of 50. Among them, 4 (9.8%) QTLs for sugars, 9 (25%) for acids and 7 (12.7%) for amino acids were stable and detected in the two successive years. We are now studying the QTLs regions in order to find candidate genes to explain differences in metabolite content in the different individuals of the population, and we expect to identify associations between genes and metabolites which will help us to understand their role in quality traits of strawberry fruit.

Candidate gene analysis for quantitative traits using the transmission disequilibrium test : the example of the melanocortin 4-receptor in pigs

Population-wide associations between loci due to linkage disequilibrium can be used to map quantitative trait loci (QTL) with high resolution. However, spurious associations between markers and QTL can also arise as a consequence of population stratification. Statistical methods that cannot differentiate between loci associations due to linkage disequilibria from those caused in other ways can render false-positive results. The transmission-disequilibrium test (TDT) is a robust test for detecting QTL. The TDT exploits within-family associations that are not affected by population stratification. However, some TDTs are formulated in a rigid-form, with reduced potential applications. In this study we generalize TDT using mixed linear models to allow greater statistical flexibility. Allelic effects are estimated with two independent parameters: one exploiting the robust within-family information and the other the potentially biased between-family information. A significant difference between these two parameters can be used as evidence for spurious association. This methodology was then used to test the effects of the fourth melanocortin receptor (MC4R) on production traits in the pig. The new analyses supported the previously reported results; i.e., the studied polymorphism is either causal of in very strong linkage disequilibrium with the causal mutation, and provided no evidence for spurious association.

Genome-Wide Association Studies of Asthma in Population-Based Cohorts Confirm Known and Suggested Loci and Identify an Additional Association near HLA

Rationale: Asthma has substantial morbidity and mortality and a strong genetic component, but identification of genetic risk factors is limited by availability of suitable studies. Objectives: To test if population-based cohorts with self-reported physician-diagnosed asthma and genome-wide association (GWA) data could be used to validate known associations with asthma and identify novel associations. Methods: The APCAT (Analysis in Population-based Cohorts of Asthma Traits) consortium consists of 1,716 individuals with asthma and 16,888 healthy controls from six European-descent population-based cohorts. We examined associations in APCAT of thirteen variants previously reported as genome-wide significant (P<5x10-8) and three variants reported as suggestive (P<5×10-7). We also searched for novel associations in APCAT (Stage 1) and followed-up the most promising variants in 4,035 asthmatics and 11,251 healthy controls (Stage 2). Finally, we conducted the first genome-wide screen for interactions with smoking or hay fever. Main Results: We observed association in the same direction for all thirteen previously reported variants and nominally replicated ten of them. One variant that was previously suggestive, rs11071559 in RORA, now reaches genome-wide significance when combined with our data (P = 2.4×10-9). We also identified two genome-wide significant associations: rs13408661 near IL1RL1/IL18R1 (PStage1+Stage2 = 1.1x10-9), which is correlated with a variant recently shown to be associated with asthma (rs3771180), and rs9268516 in the HLA region (PStage1+Stage2 = 1.1x10-8), which appears to be independent of previously reported associations in this locus. Finally, we found no strong evidence for gene-environment interactions with smoking or hay fever status. Conclusions: Population-based cohorts with simple asthma phenotypes represent a valuable and largely untapped resource for genetic studies of asthma. © 2012 Ramasamy et al.

Functionally associated molecular genetic marker map construction in perennial ryegrass (Lolium perenne L.)

A molecular marker-based map of perennial ryegrass (Lolium perenne L.) has been constructed through the use of polymorphisms associated with expressed sequence tags (ESTs). A pair-cross between genotypes from a North African ecotype and the cultivar Aurora was used to generate a two-way pseudo-testcross population. A selection of 157 cDNAs assigned to eight different functional categories associated with agronomically important biological processes was used to detect polymorphic EST–RFLP loci in the F1(NA6 × AU6) population. A comprehensive set of EST–SSR markers was developed from the analysis of 14,767 unigenes, with 310 primer pairs showing efficient amplification and detecting 113 polymorphic loci. Two parental genetic maps were produced: the NA6 genetic map contains 88 EST–RFLP and 71 EST–SSR loci with a total map length of 963 cM, while the AU6 genetic map contains 67 EST–RFLP and 58 EST–SSR loci with a total map length of 757 cM. Bridging loci permitted the alignment of homologous chromosomes between the parental maps, and a sub-set of genomic DNA-derived SSRs was used to relate linkage groups to the perennial ryegrass reference map. Regions of segregation distortion were identified, in some instances in common with other perennial ryegrass maps. The EST-derived marker-based map provides the basis for in silico comparative genetic mapping, as well as the evaluation of co-location between QTLs and functionally associated genetic loci.

Genetic Impacts of the Hull on Barley Grain Quality

Barley hull plays an important role in malt and feed quality and processing. In this study we measured the variation in hull con-tent along with other grain quality traits namely, kernel discolouration and degree of pre-harvest sprouting, in a single map-ping population. There were significant (p < 0.05) genetic as well as environment effects. In addition, heritability was calculated for hull content to be 29% and 47% for two years’ data. From the analysis, major QTL markers were identified in con-trolling the expression of hull content on chromosomes 2 (2H), and 6 (6H) with significant (P < 0.05) LOD scores of 5.4 and 3.46 respectively. Minor QTLs were identified on 1 (7H), 4 (4H), 5 (1H) and 7 (5H). The region at marker Bmac310 on 4(4H) could be associated with dormancy gene SD4. A number of the QTLs also coincided with regions for either kernel discolouration or preharvest sprouting resistance (dormancy). The results indicate that variation exists for hull content, which is influenced by both growing environment as well as genetically, although the genetic variance explained less than half of the total variance. Further, hull content also impacts on other grain quality attributes including dormancy, sprouting resistance and kernel appearance.

Rice molecular breeding laboratories in the genomics era: Current status and future considerations

Using DNA markers in plant breeding with marker-assisted selection (MAS) could greatly improve the precision and efficiency of selection, leading to the accelerated development of new crop varieties. The numerous examples of MAS in rice have prompted many breeding institutes to establish molecular breeding labs. The last decade has produced an enormous amount of genomics research in rice, including the identification of thousands of QTLs for agronomically important traits, the generation of large amounts of gene expression data, and cloning and characterization of new genes, including the detection of single nucleotide polymorphisms. The pinnacle of genomics research has been the completion and annotation of genome sequences for indica and japonica rice. This information-coupled with the development of new genotyping methodologies and platforms, and the development of bioinformatics databases and software tools-provides even more exciting opportunities for rice molecular breeding in the 21st century. However, the great challenge for molecular breeders is to apply genomics data in actual breeding programs. Here, we review the current status of MAS in rice, current genomics projects and promising new genotyping methodologies, and evaluate the probable impact of genomics research. We also identify critical research areas to "bridge the application gap" between QTL identification and applied breeding that need to be addressed to realize the full potential of MAS, and propose ideas and guidelines for establishing rice molecular breeding labs in the postgenome sequence era to integrate molecular breeding within the context of overall rice breeding and research programs.

How accurate are the marker orders in crop linkage maps generated from large marker datasets?

Marker ordering during linkage map construction is a critical component of QTL mapping research. In recent years, high-throughput genotyping methods have become widely used, and these methods may generate hundreds of markers for a single mapping population. This poses problems for linkage analysis software because the number of possible marker orders increases exponentially as the number of markers increases. In this paper, we tested the accuracy of linkage analyses on simulated recombinant inbred line data using the commonly used Map Manager QTX (Manly et al. 2001: Mammalian Genome 12, 930-932) software and RECORD (Van Os et al. 2005: Theoretical and Applied Genetics 112, 30-40). Accuracy was measured by calculating two scores: % correct marker positions, and a novel, weighted rank-based score derived from the sum of absolute values of true minus observed marker ranks divided by the total number of markers. The accuracy of maps generated using Map Manager QTX was considerably lower than those generated using RECORD. Differences in linkage maps were often observed when marker ordering was performed several times using the identical dataset. In order to test the effect of reducing marker numbers on the stability of marker order, we pruned marker datasets focusing on regions consisting of tightly linked clusters of markers, which included redundant markers. Marker pruning improved the accuracy and stability of linkage maps because a single unambiguous marker order was produced that was consistent across replications of analysis. Marker pruning was also applied to a real barley mapping population and QTL analysis was performed using different map versions produced by the different programs. While some QTLs were identified with both map versions, there were large differences in QTL mapping results. Differences included maximum LOD and R-2 values at QTL peaks and map positions, thus highlighting the importance of marker order for QTL mapping

Quantitative and molecular genetics of juvenile wood traits in radiata and slash/Caribbean pines.

The Juvenile Wood Initiative (JWI) project has been running successfully since July 2003 under a Research Agreement with FWPA and Letters of Association with the consortium partners STBA (Southern Tree Breeding Association), ArborGen and FPQ (Forestry Plantations Queensland). Over the last five and half years, JWI scientists in CSIRO, FPQ, and STBA have completed all 12 major milestones and 28 component milestones according to the project schedule. We have made benchmark progress in understanding the genetic control of wood formation and interrelationships among wood traits. The project has made 15 primary scientific findings and several results have been adopted by industry as summarized below. This progress was detailed in 10 technical reports to funding organizations and industry clients. Team scientists produced 16 scientific manuscripts (8 published, 1 in press, 2 submitted, and several others in the process of submission) and 15 conference papers or presentations. Primary Scientific Findings. The 15 major scientific findings related to wood science, inheritance and the genetic basis of juvenile wood traits are: 1. An optimal method to predict stiffness of standing trees in slash/Caribbean pine is to combine gravimetric basic density from 12 mm increment cores with a standing tree prediction of MoE using a time of flight acoustic tool. This was the most accurate and cheapest way to rank trees for breeding selection for slash/Caribbean hybrid pine. This method was also recommended for radiata pine. 2. Wood density breeding values were predicted for the first time in the STBA breeding population using a large sample of 7,078 trees (increment cores) and it was estimated that selection of the best 250 trees for deployment will produce wood density gains of 12.4%. 3. Large genetic variation for a suite of wood quality traits including density, MFA, spiral grain, shrinkage, acoustic and non-acoustic stiffness (MoE) for clear wood and standing trees were observed. Genetic gains of between 8 and 49% were predicted for these wood quality traits with selection intensity between 1 to 10% for radiata pine. 4. Site had a major effect on juvenile-mature wood transition age and the effect of selective breeding for a shorter juvenile wood formation phase was only moderate (about 10% genetic gain with 10% selection intensity, equivalent to about 2 years reduction of juvenile wood). 5. The study found no usable site by genotype interactions for the wood quality traits of density, MFA and MoE for both radiata and slash/Caribbean pines, suggesting that assessment of wood properties on one or two sites will provide reliable estimates of the genetic worth of individuals for use in future breeding. 6. There were significant and sizable genotype by environment interactions between the mainland and Tasmanian regions and within Tasmania for DBH and branch size. 7. Strong genetic correlations between rings for density, MFA and MoE for both radiata and slash/Caribbean pines were observed. This suggests that selection for improved wood properties in the innermost rings would also result in improvement of wood properties in the subsequent rings, as well as improved average performance of the entire core. 8. Strong genetic correlations between pure species and hybrid performance for each of the wood quality traits were observed in the hybrid pines. Parental performance can be used to identify the hybrid families which are most likely to have superior juvenile wood properties of the slash/Caribbean F1 hybrid in southeast Queensland. 9. Large unfavourable genetic correlations between growth and wood quality traits were a prominent feature in radiata pine, indicating that overcoming this unfavourable genetic correlation will be a major technical issue in progressing radiata pine breeding. 10. The project created the first radiata pine 18 k cDNA microarray and generated 5,952 radiata pine xylogenesis expressed sequence tags (ESTs) which assembled into 3,304 unigenes. 11. A total of 348 genes were identified as preferentially expressed genes in earlywood or latewood while a total of 168 genes were identified as preferentially expressed genes in either juvenile or mature wood. 12. Juvenile earlywood has a distinct transcriptome relative to other stages of wood development. 13. Discovered rapid decay of linkage disequilibrium (LD) in radiata pine with LD decaying to approximately 50% within 1,700 base pairs (within a typical gene). A total of 913 SNPS from sequencing 177,380 base pairs were identified for association genetic studies. 14. 149 SNPs from 44 genes and 255 SNPs from a further 51 genes (total 95 genes) were selected for association analysis with 62 wood traits, and 30 SNPs were shortlisted for their significant association with variation of wood quality traits (density, MFA and MoE) with individual significant SNPs accounting for between 1.9 and 9.7% of the total genetic variation in traits. 15. Index selection using breeding objectives was the most profitable selection method for radiata pine, but in the long term it may not be the most effective in dealing with negative genetic correlations between wood volume and quality traits. A combination of economic and biological approaches may be needed to deal with the strong adverse correlation.

Genome-wide enrichment analysis between endometriosis and obesity-related traits reveals novel susceptibility loci

Endometriosis is a chronic inflammatory condition in women that results in pelvic pain and subfertility, and has been associated with decreased body mass index (BMI). Genetic variants contributing to the heritable component have started to emerge from genome-wide association studies (GWAS), although the majority remain unknown. Unexpectedly, we observed an intergenic locus on 7p15.2 that was genome-wide significantly associated with both endometriosis and fat distribution (waist-to-hip ratio adjusted for BMI; WHRadjBMI) in an independent meta-GWAS of European ancestry individuals. This led us to investigate the potential overlap in genetic variants underlying the aetiology of endometriosis, WHRadjBMI and BMI using GWAS data. Our analyses demonstrated significant enrichment of common variants between fat distribution and endometriosis (P = 3.7 x 10(-3)), which was stronger when we restricted the investigation to more severe (Stage B) cases (P = 4.5 x 10(-4)). However, no genetic enrichment was observed between endometriosis and BMI (P = 0.79). In addition to 7p15.2, we identify four more variants with statistically significant evidence of involvement in both endometriosis and WHRadjBMI (in/near KIFAP3, CAB39L, WNT4, GRB14); two of these, KIFAP3 and CAB39L, are novel associations for both traits. KIFAP3, WNT4 and 7p15.2 are associated with the WNT signalling pathway; formal pathway analysis confirmed a statistically significant (P = 6.41 x 10(-4)) overrepresentation of shared associations in developmental processes/WNT signalling between the two traits. Our results demonstrate an example of potential biological pleiotropy that was hitherto unknown, and represent an opportunity for functional follow-up of loci and further cross-phenotype comparisons to assess how fat distribution and endometriosis pathogenesis research fields can inform each other.