Null Markers Research Articles

Characterization of a novel Wx-A1b′ null allele and PCR markers for allele identification at three Wx loci

Characterization of a novel Wx-A1b′ null allele and PCR markers for allele identification at three Wx loci

INDEFINITENESS AND DEFINITENESS IN WAIJEWA

In a language a noun phrase may be presented with an element to show whether the noun phrase definite or indefinite. Every language has its own way to show definite and indefinite, for example using certain words or attaching affixes on the nouns. Waijewa, a minority language in Sumba, East Nusa Tenggara differentiates the definite and indefinite noun phrase by attaching grammatical and morphological markers to denote definite and indefinite noun phrases. The indefinite noun phrases are ones with null markers and ones with article, while definite noun phrases are marked by the use of demonstratives, genitive case, and definite emphasizing markers. Demonstratives in Waijewa are object- distance-speaker –listener- oriented. The definiteness or indefiniteness of the nouns denoted can be anaphoric and cataphoric.

Marker-assisted stacking of null Kunitz trypsin inhibitor and off-flavour generating lipoxygenase-2 in soybean

AbstractSoybean varieties genetically free from Kunitz trypsin inhibitor (KTI) and lipoxygenase-2 (Lox2) are desirable to increase human consumption, as the former is an antinutritional factor that affects protein digestibility while the latter is a principal contributor to off-flavour. In the present investigation, soybean genotypes free from both these undesirable components were developed by introgression of null allele of Lox2 from NRC109 (lox2lox2) into two KTI-free soybean genotypes derived from genotypes JS97-52 and NRC7. Foreground selection of plants in F1, F2, BC1F1, BC1F2, BC2F1 and BC2F2 generations developed from two cross combinations i.e. NRC7-derived KTI-free genotype (N7KTIF)×NRC109 (parental combination 1) and JS97-52 derived KTI free genotype (JKTIF)×NRC109 (parental combination 2) was performed using null allele specific markers and tightly linked simple sequence repeat (SSR) markers for both KTI and Lox2 genes for the identification of homozygous recessive (titilox2lox2) plants. Background selection was performed using 239 and 241 polymorphic SSR markers across the genome. This resulted in the development of 9 and 13 soybean lines stacked for null alleles of both KTI and Lox2 (titilox2lox2) exhibiting recurrent parent genome content more than 97 and 96%, respectively. Days-to-flowering, days-to-maturity, 100-seed weight and yield per plant of the stacked lines developed from both the parental combinations were at par with the respective recurrent parents.

Use of exemplification in ESL students’ self-assessment reports: Can they help to argue better?

Abstract Self-assessment reports are a type of alternative assessment and provide a gateway of formative assessment by which learners get opportunities to reflect on their learning process and assess it, provided they are aware of their abilities and progress. In this exploratory study, we examine the self-assessment reports of 12 adult ESL learners enrolled in an Indian university programme where they assess the course content and language gains (reading and writing) from the course. Based on a mixed method of analysis, the learners were found to use exemplification to suit their discourse style. A quantitative analysis showed that the learners were using a variety of exemplification techniques like (i) brief examples with (a) phrases and (b) sentences; (ii) extended examples; and (iii) testimonials to support and argue for their assessments. Furthermore, the learners were found to use these different types of exemplification according to the levels of unity or coherence in their reports, which were at three levels – low (16 %), medium (50 %), and high unity (34 %). For instance, the presence of the first two sub-types of exemplification was found to be more frequent across the learners of low and medium unity whereas the last two types were more prevalent in the high text unity group of learners. A one-way goodness of fit chi-square test revealed that the two frequent sub-types were well distributed for the entire group as well as for the learners whose essays achieved low and medium unity while for the learners who achieved high unity the distribution was equal. Furthermore, a qualitative analysis of a few excerpts showed the types and purposes of using exemplification with 23 % overt and 77 % null markers; it was interesting to note that the null markers did not affect the communicative content of the reports as the learners were found to use other syntactic strategies to mark the presence of exemplification like listing of ideas and using wh-question markers preceding the ideas. A few instances of personalized anecdotal experiences showed that learners were using exemplification to substantiate their arguments at a high level. What is implied from this analysis is that such semi-formal self-assessment reports can be used for two purposes: to assess a course and document learner growth and orientation towards learning, and through the assessment task, trigger a linguistic gain such as develop argumentation skills in adult ESL learners.

SQL schema design: foundations, normal forms, and normalization

Normalization helps us find a database schema at design time that can process the most frequent updates efficiently at run time. Unfortunately, relational normalization only works for idealized database instances in which duplicates and null markers are not present. On one hand, these features occur frequently in real-world data compliant with the industry standard SQL, and especially in modern application domains. On the other hand, the features impose challenges that make it difficult to extend the existing forty year old normalization framework to SQL, and any current extensions are fairly limited.We introduce a new class of functional dependencies and show that they provide the right notion for SQL schema design. Axiomatic and linear-time algorithmic characterizations of the associated implication problem are established. These foundations enable us to propose a Boyce–Codd normal form for SQL. We justify the normal form by showing that it permits precisely those SQL instances which are free from data redundancy. Unlike the relational case, there are SQL schemata that cannot be converted into Boyce–Codd normal form. Nevertheless, for an expressive sub-class of our functional dependencies we establish a normalization algorithm that always produces a schema in Value-Redundancy free normal form. This normal form permits precisely those instances which are free from any redundant data value occurrences other than the null marker. Experiments show that our functional dependencies occur frequently in real-world data and that they are effective in eliminating redundant values from these data sets without loss of information.

Association between molecular markers and behavioral phenotypes in the immatures of a butterfly

Newly hatched caterpillars of the butterfly Heliconius erato phyllis routinely cannibalize eggs. In a manifestation of kin recognition they cannibalize sibling eggs less frequently than unrelated eggs. Previous work has estimated the heritability of kin recognition in H. erato phyllis to lie between 14 and 48%. It has furthermore been shown that the inheritance of kin recognition is compatible with a quantitative model with a threshold. Here we present the results of a preliminary study, in which we tested for associations between behavioral kin recognition phenotypes and AFLP and SSR markers. We implemented two experimental approaches: (1) a cannibalism test using sibling eggs only, which allowed for only two behavioral outcomes (cannibal and non-cannibal), and (2) a cannibalism test using two sibling eggs and one unrelated egg, which allowed four outcomes [cannibal who does not recognize siblings, cannibal who recognizes siblings, “super-cannibal” (cannibal of both eggs), and “super non-cannibal” (does not cannibalize eggs at all)]. Single-marker analyses were performed using χ2 tests and logistic regression with null markers as covariates. Results of the χ2 tests identified 72 associations for experimental design 1 and 73 associations for design 2. Logistic regression analysis of the markers found to be significant in the χ2 test resulted in 20 associations for design 1 and 11 associations for design 2. Experiment 2 identified markers that were more frequently present or absent in cannibals who recognize siblings and super non-cannibals; i.e. in both phenotypes capable of kin recognition.

The temporal interpretation of tenseless relative clauses in Korean

This paper investigates the temporal interpretation of Korean relative clauses that are not morphologically marked with overt tense morphemes (plain KRCs). Previous researchers (e.g. Lee in Tense, aspect, and modality: a discourse-pragmatic analysis of verbal affixes in Korean from a typological perspective. Ph.D. thesis, UCLA, 1991, Stud Lang 17: 75–110, 1993; Yoon in Temporal adverbials and Aktionsarten in Korean. Ph.D. thesis, The Ohio State University, 1996) have postulated phonologically null temporal markers in plain KRCs, and have accounted for their temporal interpretation in terms of the meaning of the postulated temporal markers. In this paper, I show that these analyses are empirically problematic, and argue that the temporal interpretation can be captured without assuming null tense or aspect, in line with Lee and Tonhauser’s (J Semant 27:307–341, 2010) tenseless analysis of the temporal interpretation of Korean and Japanese coordination constructions. I show that the temporal interpretation of plain KRCs is determined by interactions among various factors such as Aktionsarten, discourse relations, discourse context, and world knowledge, and propose a compositional analysis of the observed facts.

Possible and certain SQL keys

Driven by the dominance of the relational model, the requirements of modern applications, and the veracity of data, we revisit the fundamental notion of a key in relational databases with NULLs. In SQL database systems primary key columns are NOT NULL by default. NULL columns may occur in unique constraints which only guarantee uniqueness for tuples which do not feature null markers in any of the columns involved, and therefore serve a different function than primary keys. We investigate the notions of possible and certain keys, which are keys that hold in some or all possible worlds that can originate from an SQL table, respectively. Possible keys coincide with the unique constraint of SQL, and thus provide a semantics for their syntactic definition in the SQL standard. Certain keys extend primary keys to include NULL columns, and thus form a sufficient and necessary condition to identify tuples uniquely, while primary keys are only sufficient for that purpose. In addition to basic characterization, axiomatization, and simple discovery approaches for possible and certain keys, we investigate the existence and construction of Armstrong tables, and describe an indexing scheme for enforcing certain keys. Our experiments show that certain keys with NULLs do occur in real-world databases, and that related computational problems can be solved efficiently. Certain keys are therefore semantically well-founded and able to maintain data quality in the form of Codd's entity integrity rule while handling the requirements of modern applications, that is, higher volumes of incomplete data from different formats.

Ultra-dense genetic map of durum wheat × wild emmer wheat developed using the 90K iSelect SNP genotyping assay

Wild emmer wheat (T. turgidum ssp. dicoccoides, genome BBAA) gene pool is an important source for wheat research and improvement. To utilize this resource, we hybridized wild emmer wheat (subpopulation judaicum, accession Zavitan) with durum wheat (T. turgidum ssp. durum, cv. Svevo) and developed an F6 recombinant inbred line (RIL) population. The wheat 90K iSelect SNP genotyping assay was used for genotyping of the RILs, detecting segregation for 16,387 polymorphic markers. The genetic map was constructed based on the genotypic data of 140 RILs and included a total of 14,088 markers grouped into 2,296 genetic loci in 14 linkage groups, corresponding to the 14 chromosomes of tetraploid wheat. The map was 2,110 cM long with an average distance of 0.92 cM between adjacent markers. The B genome was slightly more polymorphic (57 %) for co-dominant SNP markers than the A genome. The map included 1,012 null allele markers, in which only one SNP allele was detected, and the frequency of these markers in the B genome of wild emmer greatly exceeded that of the A genome (69 and 31 %, respectively), which may reflect a greater rate of genomic changes in the B genome. Comparison of our mapped SNP sequences with the barley genome revealed that most of the markers (92.4 %) were syntenic. This ultra-dense SNP-based genetic map with a high level of synteny to barley provides a useful framework for genetic analyses of important traits, positional cloning and marker-assisted selection, as well as for comparative genomics and genome organization studies in wheat and other cereals.

Functional Dependencies with null Markers

Functional dependencies are an integral part of database design. However, they are only defined when we exclude null markers. Yet we commonly use null markers in practice. To bridge this gap between theory and practice, researchers have proposed definitions of functional dependencies over relations with null markers. Though sound, these definitions lack some qualities that we find desirable. For example, some fail to satisfy Armstrong's axioms---while these axioms are part of the foundation of common database methodologies. We propose a set of properties that any extension of functional dependencies over relations with null markers should possess. We then propose two new extensions having these properties. These extensions attempt to allow null markers where they make sense to practitioners. They both support Armstrong's axioms and provide realizable null markers: at any time, some or all of the null markers can be replaced by actual values without causing an anomaly. Our proposals may improve database designs.

Development and Application of Genomic Control Methods for Genome-Wide Association Studies Using Non-Additive Models

Genome-wide association studies (GWAS) comprise a powerful tool for mapping genes of complex traits. However, an inflation of the test statistic can occur because of population substructure or cryptic relatedness, which could cause spurious associations. If information on a large number of genetic markers is available, adjusting the analysis results by using the method of genomic control (GC) is possible. GC was originally proposed to correct the Cochran-Armitage additive trend test. For non-additive models, correction has been shown to depend on allele frequencies. Therefore, usage of GC is limited to situations where allele frequencies of null markers and candidate markers are matched. In this work, we extended the capabilities of the GC method for non-additive models, which allows us to use null markers with arbitrary allele frequencies for GC. Analytical expressions for the inflation of a test statistic describing its dependency on allele frequency and several population parameters were obtained for recessive, dominant, and over-dominant models of inheritance. We proposed a method to estimate these required population parameters. Furthermore, we suggested a GC method based on approximation of the correction coefficient by a polynomial of allele frequency and described procedures to correct the genotypic (two degrees of freedom) test for cases when the model of inheritance is unknown. Statistical properties of the described methods were investigated using simulated and real data. We demonstrated that all considered methods were effective in controlling type 1 error in the presence of genetic substructure. The proposed GC methods can be applied to statistical tests for GWAS with various models of inheritance. All methods developed and tested in this work were implemented using R language as a part of the GenABEL package.

Correcting for differential genotyping error in genetic association analysis

Differential genotype error in case-control association studies occurs when cases and controls are genotyped under different conditions. Existence of differential errors can considerably bias the association test, resulting in inflation of type I error and spurious significance. With the availability of high-throughput genotyping technologies such as the SNPchip, null markers that are unlinked with the disease can be used to correct for the bias caused by differential errors. A similar method, known as the genomic control, had been used to correct for population stratification in association studies. In this paper, we show that the same idea can be used to correct for the bias caused by differential errors, under the assumption that the null markers and the candidate marker are subject to the same or similar genotyping error model. The variance inflation is shown to be minor and the bias in the association test is the major source of type I error inflation in the presence of differential errors. Our method centralizes the test statistic by deducting the bias estimated from null markers through a quadratic regression method, which adjusts for the variability of null marker allele frequencies. Simulation results show that the proposed method performs very well in correcting for the type I error inflations.

The implication problem of data dependencies over SQL table definitions

We investigate the implication problem for classes of data dependencies over SQL table definitions. Under Zaniolo's “no information” interpretation of null markers we establish an axiomatization and algorithms to decide the implication problem for the combined class of functional and multivalued dependencies in the presence of NOT NULL constraints. The resulting theory subsumes three previously orthogonal frameworks. We further show that the implication problem of this class is equivalent to that in a propositional fragment of Schaerf and Cadoli's [1995] family of para-consistent S-3 logics. In particular, S is the set of variables that correspond to attributes declared NOT NULL. We also show how our equivalences for multivalued dependencies can be extended to Delobel's class of full first-order hierarchical decompositions, and the equivalences for functional dependencies can be extended to arbitrary Boolean dependencies. These dualities allow us to transfer several findings from the propositional fragments to the corresponding classes of data dependencies, and vice versa. We show that our results also apply to Codd's null interpretation “value unknown at present”, but not to Imielinski's [1989] or-relations utilizing Levene and Loizou's weak possible world semantics [Levene and Loizou 1998]. Our findings establish NOT NULL constraints as an effective mechanism to balance not only the certainty in database relations but also the expressiveness with the efficiency of entailment relations. They also control the degree by which the implication of data dependencies over total relations is soundly approximated in SQL table definitions.

Correcting for biases in affected sib-pair linkage analysis caused by uncertainty in sibling relationship

When there is uncertainty in sibling relationship, the classical affected sib-pair (ASP) linkage tests may be severely biased. This can happen, for example, if some of the half sib-pairs are mixed with full sib-pairs. The genomic control method has been used in association analysis to adjust for population structures. We show that the same idea can be applied to ASP linkage analysis with uncertainty in sibling relationship. Assuming that, in addition to the candidate marker, null markers that are unlinked to the disease locus are also genotyped, we may use the information on these loci to estimate the proportion of half sib-pairs and to correct for the bias and variance distortion caused by the heterogeneity of sibling relationship. Unlike in association studies, the null loci are not required to be matched with the candidate marker in allele frequency for ASP linkage analysis. This makes our approach flexible in selecting null markers. In our simulations, using a number of 30 or more null loci can effectively remove the bias and variance distortion. It is also shown that, even the null loci are weakly linked to the disease locus, the proposed method can also provide satisfactory correction.

Identification of microsatellite markers linked to leaf rust resistance gene Lr25 in wheat

The leaf rust resistance gene Lr25, transferred from Secale cereale L. into wheat and located on chromosome 4B, imparts resistance to all pathotypes of leaf rust in South-East Asia. In an F(2)-derived F(3) population, created by crossing TcLr25 that carries the gene Lr25 for leaf rust resistance with leaf rust-susceptible parent Agra Local, three microsatellite markers located on the long arm of chromosome 4B were found to be linked to the Lr25 locus. The donor parent TcLr25 is a near-isogenic line derived from the variety Thatcher. The most virulent pathotype of leaf rust in the South-East Asian region, designated 77-5 (121R63-1), was used for challenging the population under artificially controlled conditions. The marker Xgwm251 behaved as a co-dominant marker placed 3.8cM away from the Lr25 locus on 4BL. Two null allele markers, Xgwm538 and Xgwm6, in the same linkage group were located at a distance of 3.8cM and 16.2cM from the Lr25 locus, respectively. The genetic sequence of Xgwm251, Lr25, Xgwm538, and Xgwm6 covered a total length of 20cM on 4BL. The markers were validated for their specificity to Lr25 resistance in a set of 43 wheat genetic stocks representing 43 other Lr genes.

Bayes factors in the presence of population stratification

Hidden population stratification (PS) is a main concern in the analysis of case-control genetic association studies. All methods to correct for hidden PS have been focused on classical hypothesis testing, and cannot be directly applied to Bayesian analysis. In this paper, to study the impact and the correction of hidden PS on Bayes factor (BF), we use a simple approximation of BF in terms of the maximum likelihood estimates of the odds ratio (OR) and its asymptotic variance. One advantage is that the commonly used principal components analysis method with a large panel of null markers scanned from existing genome-wide association studies can be directly employed to correct for hidden PS in estimating the OR and its asymptotic variance, through which a correction to BF for hidden PS can be achieved. Using simulations, we examine the impact of ignoring hidden PS on BF and show that the proposed method yields an appropriate correction in Bayesian analysis.

A triple combination strategy corrects population stratification bias and saves genotyping cost

Objective The case-control association study has gained popularity for mapping disease-susceptibility gene(s) of complex human diseases. However, the study is prone to population stratification bias. Study Design and Setting The authors proposed a triple combination strategy of stratum matching, genomic control, and multiple DNA pooling for population-based case-control association studies. Monte Carlo simulation showed that the type I error rates are well controlled using this strategy. Results As for power, it increases under the following situations: (1) more accurate stratum matching, (2) more null markers for genomic control, (3) more DNA pooling sets, and (4) more accurate DNA pooling measurement. Conclusion The triple combination strategy corrects population stratification bias and saves genotyping cost.

Delta-Centralization Fails to Control for Population Stratification in Genetic Association Studies

Objective: To investigate the validity of simulations and assumptions used to underpin the delta-centralization (DC) method for correcting for population stratification in genetic association studies; to assess the effectiveness of DC compared to genomic control (GC) under valid simulation conditions; and to highlight other studies employing similarly flawed simulations. Methods: DC and GC use data from unlinked null loci to correct the test statistic at the target locus, but differ in the way the correction is performed. We compare DC and GC under two simulation approaches: an invalid approach adopted by the originators of DC, which permits subpopulation allele frequency matching of null markers to the target locus; and a valid approach, based on the Balding-Nichols model, which does not allow subpopulation matching. Results: DC works under invalid simulation conditions (subpopulation allele frequency matching), but not under our valid ones. We use theoretical arguments to assert that there are no valid conditions under which DC might work. We identify several studies which have adopted similarly invalid simulation approaches in this field. Conclusion: DC fails to control for population stratification and should not be used. Other results from studies which have used the same invalid simulation approach should be treated cautiously.

Correcting for cryptic relatedness by a regression-based genomic control method

BackgroundGenomic control (GC) method is a useful tool to correct for the cryptic relatedness in population-based association studies. It was originally proposed for correcting for the variance inflation of Cochran-Armitage's additive trend test by using information from unlinked null markers, and was later generalized to be applicable to other tests with the additional requirement that the null markers are matched with the candidate marker in allele frequencies. However, matching allele frequencies limits the number of available null markers and thus limits the applicability of the GC method. On the other hand, errors in genotype/allele frequencies may cause further bias and variance inflation and thereby aggravate the effect of GC correction.ResultsIn this paper, we propose a regression-based GC method using null markers that are not necessarily matched in allele frequencies with the candidate marker. Variation of allele frequencies of the null markers is adjusted by a regression method.ConclusionThe proposed method can be readily applied to the Cochran-Armitage's trend tests other than the additive trend test, the Pearson's chi-square test and other robust efficiency tests. Simulation results show that the proposed method is effective in controlling type I error in the presence of population substructure.

Genetic evidence for ubiquitin-specific proteasesUSP24andUSP40as candidate genes for late-onset Parkinson disease

Linkage studies have defined susceptibility regions for late-onset Parkinson disease (PD) on chromosomes 1 and 2, but specific genetic variants have not been definitively identified. Here we report the results of a case-control study to identify disease-associated single nucleotide polymorphisms (SNPs) in these loci. In the initial phase of our study, we genotyped two putative functional SNPs in ubiquitin-specific protease 24 (USP24), a biological candidate gene within the chromosome 1 linkage region, and scanned the chromosome 2 linkage peak with 43 SNPs in a sample set of 224 PD cases and 186 matched controls. Both USP24 SNPs were significantly associated with disease risk (p = 0.0037 for rs1165222:T > C, p.Thr195ILe, and p = 0.037 for rs13312:C > G, a SNP in the 3'-untranslated region), and one marker, rs1048603:C > T, p.Arg1123Cys, in USP40 was significant from the chromosome 2 scan (p = 0.038). Further genotyping of the region surrounding these initial markers led us to identify 19 additional SNPs with strong disease association. In the second phase, we genotyped the 22 significant markers in an additional 110 cases and 162 controls, which together with part of the initial sample set (201 cases and 149 controls) constitute an expanded sample set of 311 age- and gender-matched case-control pairs. Twenty-one markers were significant in the expanded sample set (most significant allelic p-value: 0.0006 for rs287235:C > G on chromosome 1, and 0.005 for rs838552:T > C on chromosome 2), and six SNPs in USP24 remained significant after conservatively adjusting for testing 27 markers (pBonferroni = 0.017-0.049). It is unlikely that population stratification contributed to this finding, as population stratification was undetectable in our sample set using 78 null markers. Our data suggest that genetic variants in USP24 and USP40 affect the risk for late-onset PD, which is consistent with the predicted role of the ubiquitination pathway in PD etiology.