Functional markers for gene mapping and genetic diversity studies in sugarcane

Abstract Background The database of sugarcane expressed sequence tags (EST) offers a great opportunity for developing molecular markers that are directly associated with important agronomic traits. The development of new EST-SSR markers represents an important tool for genetic analysis. In sugarcane breeding programs, functional markers can be used to accelerate the process and select important agronomic traits, especially in the mapping of quantitative traits loci (QTL) and plant resistant pathogens or qualitative resistance loci (QRL). The aim of this work was to develop new simple sequence repeat (SSR) markers in sugarcane using the sugarcane expressed sequence tag (SUCEST database). Findings A total of 365 EST-SSR molecular markers with trinucleotide motifs were developed and evaluated in a collection of 18 genotypes of sugarcane (15 varieties and 3 species). In total, 287 of the EST-SSRs markers amplified fragments of the expected size and were polymorphic in the analyzed sugarcane varieties. The number of alleles ranged from 2-18, with an average of 6 alleles per locus, while polymorphism information content values ranged from 0.21-0.92, with an average of 0.69. The discrimination power was high for the majority of the EST-SSRs, with an average value of 0.80. Among the markers characterized in this study some have particular interest, those that are related to bacterial defense responses, generation of precursor metabolites and energy and those involved in carbohydrate metabolic process. Conclusions These EST-SSR markers presented in this work can be efficiently used for genetic mapping studies of segregating sugarcane populations. The high Polymorphism Information Content (PIC) and Discriminant Power (DP) presented facilitate the QTL identification and marker-assisted selection due the association with functional regions of the genome became an important tool for the sugarcane breeding program.

Lumbar intervertebral disc abnormalities: comparison of quantitative T2 mapping with conventional MR at 3.0 T

To assess the relationship of morphologically defined lumbar disc abnormalities with quantitative T2 mapping.

Quantitative T2 mapping of knee cartilage: differentiation of healthy control cartilage and cartilage repair tissue in the knee with unloading - initial results

Purpose: To prospectively determine on T2 cartilage maps the effect of unloading during a clinical magnetic resonance (MR) examination in the postoperative follow-up of patients after matrix-associated autologous chondrocyte transplantation (MACT) of the knee joint. Materials and Methods: Ethical approval for this study was provided by the local ethics commission, and written informed consent was obtained. Thirty patients (mean age, 35.4 years +/- 10.5) with a mean postoperative follow-up period of 29.1 months +/- 24.4 were enrolled. A multiecho spin-echo T2-weighted sequence was performed at the beginning (early unloading) and end (late unloading) of the MR examination, with an interval of 45 minutes. Mean and zonal region of interest T2 measurements were obtained in control cartilage and cartilage repair tissue. Statistical analysis of variance was performed. Results: The change in T2 values of control cartilage (early unloading, 50.2 msec +/- 8.4; late unloading, 51.3 msec +/- 8.5) was less pronounced than the change in T2 values of cartilage repair tissue (early unloading, 51.8 msec +/- 11.7; late unloading, 56.1 msec +/- 14.4) (P = .024). The difference between control cartilage and cartilage repair tissue was not significant for early unloading (P = .314) but was significant for late unloading (P = .036). Zonal T2 measurements revealed a higher dependency on unloading for the superficial cartilage layer. Conclusion: Our results suggest that T2 relaxation can be used to assess early and late unloading values of articular cartilage in a clinical setting and that the time point of the quantitative T2 measurement affects the differentiation between native and abnormal articular cartilage. (c) RSNA, 2010.

Detection of degenerative cartilage disease: comparison of high-resolution morphological MR and quantitative T2 mapping at 3.0 Tesla

The aim of the study was to investigate the association of T2 relaxation times of the knee with early degenerative cartilage changes. Furthermore the impact of unloading the knee on T2 values was evaluated.

Mapping of a new locus for congenital anomalies of the kidney and urinary tract on chromosome 8q24

Congenital anomalies of the kidney and urinary tract (CAKUT) account for the majority of end-stage renal disease in children (50%). Previous studies have mapped autosomal dominant loci for CAKUT. We here report a genome-wide search for linkage in a large pedigree of Somalian descent containing eight affected individuals with a non-syndromic form of CAKUT.

Quantitative mapping of T2 using partial spoiling

Fast quantitative MRI has become an important tool for biochemical characterization of tissue beyond conventional T1, T2, and T2*-weighted imaging. As a result, steady-state free precession (SSFP) techniques have attracted increased interest, and several methods have been developed for rapid quantification of relaxation times using steady-state free precession. In this work, a new and fast approach for T2 mapping is introduced based on partial RF spoiling of nonbalanced steady-state free precession. The new T2 mapping technique is evaluated and optimized from simulations, and in vivo results are presented for human brain at 1.5 T and for human articular cartilage at 3.0 T. The range of T2 for gray and white matter was from 60 msec (for the corpus callosum) to 100 msec (for cortical gray matter). For cartilage, spatial variation in T2 was observed between deep (34 msec) and superficial (48 msec) layers, as well as between tibial (33 msec), femoral, (54 msec) and patellar (43 msec) cartilage. Excellent correspondence between T2 values derived from partially spoiled SSFP scans and the ones found with a reference multicontrast spin-echo technique is observed, corroborating the accuracy of the new method for proper T2 mapping. Finally, the feasibility of a fast high-resolution quantitative partially spoiled SSFP T2 scan is demonstrated at 7.0 T for human patellar cartilage.

Quantitative T2 mapping of the patella at 3.0T is sensitive to early cartilage degeneration, but also to loading of the knee

The aim of the study was to explore the sensitivity and robustness of T2 mapping in the detection and quantification of early degenerative cartilage changes at the patella.

Quantitative T2 mapping during follow-up after matrix-associated autologous chondrocyte transplantation (MACT): full-thickness and zonal evaluation to visualize the maturation of cartilage repair tissue

The purpose of this article was to evaluate the potential of in vivo zonal T2-mapping as a noninvasive tool in the longitudinal visualization of cartilage repair tissue maturation after matrix-associated autologous chondrocyte transplantation (MACT). Fifteen patients were treated with MACT and evaluated cross-sectionally, with a baseline MRI at a follow-up of 19.7 +/- 12.1 months after cartilage transplantation surgery of the knee. In the same 15 patients, 12 months later (31.7 +/- 12.0 months after surgery), a longitudinal 1-year follow-up MRI was obtained. MRI was performed on a 3 Tesla MR scanner; morphological evaluation was performed using a double-echo steady-state sequence; T2 maps were calculated from a multiecho, spin-echo sequence. Quantitative mean (full-thickness) and zonal (deep and superficial) T2 values were calculated in the cartilage repair area and in control cartilage sites. A statistical analysis of variance was performed. Full-tickness T2 values showed no significant difference between sites of healthy cartilage and cartilage repair tissue (p < 0.05). Using zonal T2 evaluation, healthy cartilage showed a significant increase from the deep to superficial cartilage layers (p < 0.05). Cartilage repair tissue after MACT showed no significant zonal increase from deep to superficial cartilage areas during baseline MRI (p > 0.05); however, during the 1-year follow-up, a significant zonal stratification could be observed (p < 0.05). Morphological evaluation showed no significant difference between the baseline and the 1-year follow-up MRI. T2 mapping seems to be more sensitive in revealing changes in the repair tissue compared to morphological MRI. In vivo zonal T2 assessment may be sensitive enough to characterize the maturation of cartilage repair tissue.

Genetic mapping of the belt pattern in Brown Swiss cattle to BTA3

The white belt pattern of Brown Swiss cattle is characterized by a lack of melanocytes in a stretch of skin around the midsection. This pattern is of variable width and sometimes the belt does not fully circle the body. To identify the gene responsible for this colour variation, we performed linkage mapping of the belted locus using six segregating half-sib families including 104 informative meioses for the belted character. The pedigree confirmed a monogenic autosomal dominant inheritance of the belted phenotype in Brown Swiss cattle. We performed a genome scan using 186 microsatellite markers in a subset of 88 animals of the six families. Linkage with the belt phenotype was detected at the telomeric region of BTA3. Fine-mapping and haplotype analysis using 19 additional markers in this region refined the critical region of the belted locus to a 922-kb interval on BTA3. As the corresponding human and mouse chromosome segments contain no obvious candidate gene for this coat colour trait, the mutation causing the belt pattern in the Brown Swiss cattle might help to identify an unknown gene influencing skin pigmentation.

Mitotic mapping of a novel tumor suppressor locus on human chromosome 3q important in osteosarcoma tumorigenesis

Tumor-specific loss of constitutional heterozygosity by deletion, mitotic recombination or nondisjunction is a common mechanism for tumor suppressor allele inactivation. When loss of heterozygosity is the result of mitotic recombination, or a segmental deletion event, only a portion of the chromosome is lost. This information can be used to map the location of new tumor suppressor genes. In osteosarcoma, the highest frequencies of loss of heterozygosity have been reported for chromosomes 3q, 13q, 17p. On chromosomes 13q and 17p, allelic losses are associated with loss of function at the retinoblastoma susceptibility locus (RB1) and the p53 locus, respectively. Chromosome 3q is also of particular interest because the high percent of loss of heterozygosity (62%-75%) suggests the presence of another tumor suppressor important for osteosarcoma tumorigenesis. To localize this putative tumor suppressor gene, we used polymorphic markers on chromosome 3q to find the smallest common region of allele loss. This putative tumor suppressor was localized to a 700 kb region on chromosome 3q26.2 between the polymorphic loci D3S1282 and D3S1246. ^

Physical and functional mapping of a novel tumor suppressor locus for prostate cancer within chromosome 10p12.31-q11

Prostate cancer remains the second leading cause of male cancer deaths in the United States, yet the molecular mechanisms underlying this disease remain largely unknown. Cytogenetic and molecular analyses of prostate tumors suggest a consistent association with the loss of chromosome 10. Previously, we have defined a novel tumor suppressor locus PAC-1 within chromosome 10pter-q11. Introduction of the short arm of chromosome 10 into a prostatic adenocarcinoma cell line PC-3H resulted in dramatic tumor suppression and restoration of a programmed cell death pathway. Using a combined approach of comparative genomic hybridization and microsatellite analysis of PC-3H, I have identified a region of hemizygosity within 10p12-p15. This region has been shown to be involved in frequent loss of heterozygosity in gliomas and melanoma. To functionally dissect the region within chromosome 10p containing PAC-1, we developed a strategy of serial microcell fusion, a technique that allows the transfer of defined fragments of chromosome 10p into PC-3H. Serial microcell fusion was used to transfer defined 10p fragments into a mouse A9 fibrosarcoma cell line. Once characterized by FISH and microsatellite analyses, the 10p fragments were subsequently transferred into PC-3H to generate a panel of microcell hybrid clones containing overlapping deletions of chromosome 10p. In vivo and microsatellite analyses of these PC hybrids identified a small chromosome 10p fragment (an estimated 31 Mb in size inclusive of the centromere) that when transferred into the PC-3H background, resulted in significant tumor suppression and limited a region of functional tumor suppressor activity to chromosome 10p12.31-q11. This region coincides with a region of LOH demonstrated in prostate cancer. These studies demonstrate the utility of this approach as a powerful tool to limit regions of functional tumor suppressor activity. Furthermore, these data used in conjunction with data generated by the Human Genome Project lent a focused approach to identify candidate tumor suppressor genes involved in prostate cancer. ^

Towards the identification of a tumor suppressor gene on chromosome 3p12: Physical mapping and candidate gene screening

Renal cell carcinoma (RCC) is the most common malignant tumor of the kidney. Characterization of RCC tumors indicates that the most frequent genetic event associated with the initiation of tumor formation involves a loss of heterozygosity or cytogenetic aberration on the short arm of human chromosome 3. A tumor suppressor locus Nonpapillary Renal Carcinoma-1 (NRC-1, OMIM ID 604442) has been previously mapped to a 5–7 cM region on chromosome 3p12 and shown to induce rapid tumor cell death in vivo, as demonstrated by functional complementation experiments. ^ To identify the gene that accounts for the tumor suppressor activities of NRC-1, fine-scale physical mapping was conducted with a novel real-time quantitative PCR based method developed in this study. As a result, NRC-1 was mapped within a 4.6-Mb region defined by two unique sequences within UniGene clusters Hs.41407 and Hs.371835 (78,545Kb–83,172Kb in the NCBI build 31 physical map). The involvement of a putative tumor suppressor gene Robo1/Dutt1 was excluded as a candidate for NRC-1. Furthermore, a transcript map containing eleven candidate genes was established for the 4.6-Mb region. Analyses of gene expression patterns with real-time quantitative RT-PCR assays showed that one of the eleven candidate genes in the interval (TSGc28) is down-regulated in 15 out of 20 tumor samples compared with matched normal samples. Three exons of this gene have been identified by RACE experiments, although additional exon(s) seem to exist. Further gene characterization and functional studies are required to confirm the gene as a true tumor suppressor gene. ^ To study the cellular functions of NRC-1, gene expression profiles of three tumor suppressive microcell hybrids, each containing a functional copy of NRC-1, were compared with those of the corresponding parental tumor cell lines using 16K oligonucleotide microarrays. Differentially expressed genes were identified. Analyses based on the Gene Ontology showed that introduction of NRC-1 into tumor cell lines activates genes in multiple cellular pathways, including cell cycle, signal transduction, cytokines and stress response. NRC-1 is likely to induce cell growth arrest indirectly through WEE1. ^

Adiposity and the perilipin gene: The role of single locus and multilocus variation, obesity-related quantitative traits, and disease-related phenotypes in the Atherosclerosis Risk in Communities (ARIC) study

Obesity is a complex multifactorial disease and is a public health priority. Perilipin coats the surface of lipid droplets in adipocytes and is believed to stabilize these lipid bodies by protecting triglyceride from early lipolysis. This research project evaluated the association between genetic variation within the human perilipin (PLIN) gene and obesity-related quantitative traits and disease-related phenotypes in Non-Hispanic White (NHW) and African American (AA) participants from the Atherosclerosis Risk in Communities (ARIC) Study. ^ Multivariate linear regression, multivariate logistic regression, and Cox proportional hazards models evaluated the association between single gene variants (rs2304794, rs894160, rs8179071, and rs2304795) and multilocus variation (rs894160 and rs2304795) within the PLIN gene and both obesity-related quantitative traits (body weight, body mass index [BMI], waist girth, waist-to-hip ratio [WHR], estimated percent body fat, and plasma total triglycerides) and disease-related phenotypes (prevalent obesity, metabolic syndrome [MetS], prevalent coronary heart disease [CHD], and incident CHD). Single variant analyses were stratified by race and gender within race while multilocus analyses were stratified by race. ^ Single variant analyses revealed that rs2304794 and rs894160 were significantly related to plasma triglyceride levels in all NHWs and NHW women. Among AA women, variant rs8179071 was associated with triglyceride levels and rs2304794 was associated with risk-raising waist circumference (>0.8 in women). The multilocus effects of variants rs894160 and rs2304795 were significantly associated with body weight, waist girth, WHR, estimated percent body fat, class II obesity (BMI ≥ 35 kg/m2), class III obesity (BMI ≥ 35 kg/m2), and risk-raising WHR (>0.9 in men and >0.8 in women) in AAs. Variant rs2304795 was significantly related to prevalent MetS among AA males and prevalent CHD in NHW women; multilocus effects of the PLIN gene were associated with prevalent CHD among NHWs. Rs2304794 was associated with incident CHD in the absence of the MetS among AAs. These findings support the hypothesis that variation within the PLIN gene influences obesity-related traits and disease-related phenotypes. ^ Understanding these effects of the PLIN genotype on the development of obesity can potentially lead to tailored health promotion interventions that are more effective. ^

THE NATURAL AND ORTHOGONAL INTERACTION (NOIA) MODELS FOR QUANTITATIVE TRAITS (QTs) AND COMPLEX DISEASES

My dissertation focuses on developing methods for gene-gene/environment interactions and imprinting effect detections for human complex diseases and quantitative traits. It includes three sections: (1) generalizing the Natural and Orthogonal interaction (NOIA) model for the coding technique originally developed for gene-gene (GxG) interaction and also to reduced models; (2) developing a novel statistical approach that allows for modeling gene-environment (GxE) interactions influencing disease risk, and (3) developing a statistical approach for modeling genetic variants displaying parent-of-origin effects (POEs), such as imprinting. In the past decade, genetic researchers have identified a large number of causal variants for human genetic diseases and traits by single-locus analysis, and interaction has now become a hot topic in the effort to search for the complex network between multiple genes or environmental exposures contributing to the outcome. Epistasis, also known as gene-gene interaction is the departure from additive genetic effects from several genes to a trait, which means that the same alleles of one gene could display different genetic effects under different genetic backgrounds. In this study, we propose to implement the NOIA model for association studies along with interaction for human complex traits and diseases. We compare the performance of the new statistical models we developed and the usual functional model by both simulation study and real data analysis. Both simulation and real data analysis revealed higher power of the NOIA GxG interaction model for detecting both main genetic effects and interaction effects. Through application on a melanoma dataset, we confirmed the previously identified significant regions for melanoma risk at 15q13.1, 16q24.3 and 9p21.3. We also identified potential interactions with these significant regions that contribute to melanoma risk. Based on the NOIA model, we developed a novel statistical approach that allows us to model effects from a genetic factor and binary environmental exposure that are jointly influencing disease risk. Both simulation and real data analyses revealed higher power of the NOIA model for detecting both main genetic effects and interaction effects for both quantitative and binary traits. We also found that estimates of the parameters from logistic regression for binary traits are no longer statistically uncorrelated under the alternative model when there is an association. Applying our novel approach to a lung cancer dataset, we confirmed four SNPs in 5p15 and 15q25 region to be significantly associated with lung cancer risk in Caucasians population: rs2736100, rs402710, rs16969968 and rs8034191. We also validated that rs16969968 and rs8034191 in 15q25 region are significantly interacting with smoking in Caucasian population. Our approach identified the potential interactions of SNP rs2256543 in 6p21 with smoking on contributing to lung cancer risk. Genetic imprinting is the most well-known cause for parent-of-origin effect (POE) whereby a gene is differentially expressed depending on the parental origin of the same alleles. Genetic imprinting affects several human disorders, including diabetes, breast cancer, alcoholism, and obesity. This phenomenon has been shown to be important for normal embryonic development in mammals. Traditional association approaches ignore this important genetic phenomenon. In this study, we propose a NOIA framework for a single locus association study that estimates both main allelic effects and POEs. We develop statistical (Stat-POE) and functional (Func-POE) models, and demonstrate conditions for orthogonality of the Stat-POE model. We conducted simulations for both quantitative and qualitative traits to evaluate the performance of the statistical and functional models with different levels of POEs. Our results showed that the newly proposed Stat-POE model, which ensures orthogonality of variance components if Hardy-Weinberg Equilibrium (HWE) or equal minor and major allele frequencies is satisfied, had greater power for detecting the main allelic additive effect than a Func-POE model, which codes according to allelic substitutions, for both quantitative and qualitative traits. The power for detecting the POE was the same for the Stat-POE and Func-POE models under HWE for quantitative traits.