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At least 1,657 records · Page 92Linked to original sources
PubMed2006

The genetic control of milling yield, dough rheology and baking quality of wheat.

Improving the end-use quality of wheat is a key target for many breeding programmes. With the exception of the relationship between glutenin alleles and some dough rheological characters, knowledge concerning the genetic control of wheat quality traits is somewhat limited. A doubled haploid population produced from a cross between two Australian cultivars 'Trident' and 'Molineux' has been used to construct a linkage map based largely on microsatellite molecular makers. 'Molineux' is superior to 'Trident' for a number of milling, dough rheology and baking quality characteristics, although by international standards 'Trident' would still be regarded as possessing moderately good end-use quality. This population was therefore deemed useful for investigation of wheat end-use quality. A number of significant QTL identified for dough rheological traits mapped to HMW and LMW glutenin loci on chromosomes 1A and 1B. However, QTL associated with dough strength and loaf volume were also identified on chromosome 2A and a significant QTL associated with loaf volume and crumb quality was identified on chromosome 3A. A QTL for flour protein content and milling yield was identified on chromosome 6A and a QTL associated with flour colour reported previously on chromosome 7B was confirmed in this population. The detection of loci affecting dough strength, loaf volume and flour protein content may provide fresh opportunities for the application of marker-assisted selection to improve bread-making quality.

Alleles↗
PubMed1995

Toward fully automated genotyping: genotyping microsatellite markers by deconvolution.

Dense genetic linkage maps have been constructed for the human and mouse genomes, with average densities of 2.9 cM and 0.35 cM, respectively. These genetic maps are crucial for mapping both Mendelian and complex traits and are useful in clinical genetic diagnosis. Current maps are largely comprised of abundant, easily assayed, and highly polymorphic PCR-based microsatellite markers, primarily dinucleotide (CA)n repeats. One key limitation of these length polymorphisms is the PCR stutter (or slippage) artifact that introduces additional stutter bands. With two (or more) closely spaced alleles, the stutter bands overlap, and it is difficult to accurately determine the correct alleles; this stutter phenomenon has all but precluded full automation, since a human must visually inspect the allele data. We describe here novel deconvolution methods for accurate genotyping that mathematically remove PCR stutter artifact from microsatellite markers. These methods overcome the manual interpretation bottleneck and thereby enable full automation of genetic map construction and use. New functionalities, including the pooling of DNAs and the pooling of markers, are described that may greatly reduce the associated experimentation requirements.

Algorithms↗
PubMed2025

Inference and visualization of complex genotype-phenotype maps with gpmap-tools.

Understanding how biological sequences give rise to observable traits, that is, how genotype maps to phenotype, is a central goal in biology. Yet our knowledge of genotype-phenotype maps in natural systems is limited due to the high dimensionality of sequence space and the context-dependent effects of mutations. The emergence of Multiplex assays of variant effect (MAVEs), along with large collections of natural sequences, offer new opportunities to empirically characterize these maps at an unprecedented scale. However, tools for statistical and exploratory analysis of these high-dimensional data are still needed. To address this gap, we developed gpmap-tools (https://github.com/cmarti/gpmap-tools), a python library that integrates a series of models for inference, phenotypic imputation, and error estimation from MAVE data or collections of natural sequences in the presence of genetic interactions of every possible order. gpmap-tools also provides methods for summarizing patterns of epistasis and visualization of genotype-phenotype maps containing up to millions of genotypes. To demonstrate its utility, we used gpmap-tools to infer genotype-phenotype maps containing 262,144 variants of the Shine-Dalgarno sequence from both genomic 5'UTR sequences and experimental MAVE data. Visualization of the inferred landscapes consistently revealed high-fitness ridges that link core motifs at different distances from the start codon. In summary, gpmap-tools provides a flexible, interpretable framework for studying complex genotype-phenotype maps, opening new avenues for understanding the architecture of genetic interactions and their evolutionary consequences.

Gaussian process↗
PubMed2004

A Leishmania major response locus identified by interval-specific congenic mapping of a T helper type 2 cell bias-controlling quantitative trait locus.

The propensity of naive CD4 T cells to become T helper (Th) type 2 cells correlates with susceptibility to infection by the protozoal parasite Leishmania major. Using genetic linkage analysis, we earlier identified Dice1 as a Th2 cell bias-controlling quantitative trait locus on chromosome 16. Using interval-specific congenic mapping, we now resolve Dice1 into two independent genetic loci, Dice1.1 and Dice1.2, which control Il4 expression from naive Th cells and thereby indirectly control Th2 cell bias. Interestingly, only one of the two congenic intervals containing Dice1.1 and Dice1.2, respectively, also contained an L. major response locus, indicating that L. major responsiveness can be insensitive to determinants that influence Th2 cell bias by controlling naive T cell Il4 expression. These results lay the groundwork for identifying the Dice1.1 and Dice1.2 genes controlling naive T cell Il4 expression and L. major responses, and for testing whether these control other Th2 cell-dependent processes such as worm expulsion, allergic asthma, and dermatitis.

Animals↗
PubMed2003

Quantitative trait locus analysis of fungal disease resistance factors on a molecular map of grapevine.

A full-sibling F1 population comprising 153 individuals from the cross of 'Regent' x 'Lemberger' was employed to construct a genetic map based on 429 molecular markers. The newly-bred red grapevine variety 'Regent' has multiple field-resistance to fungal diseases inherited as polygenic traits, while 'Lemberger' is a traditional fungus-susceptible cultivar. The progeny segregate quantitatively for resistances to Plasmopara viticola and Uncinula necator, fungal pathogens that threaten viticulture in temperate areas. A double pseudo-testcross strategy was employed to construct the two parental maps under high statistical stringency for linkage to obtain a robust marker frame for subsequent quantitative trait locus (QTL) analysis. In total, 185 amplified fragment length polymorphism, 137 random amplified polymorphic DNA, 85 single sequence repeat and 22 sequence characterized amplified region or cleaved amplified polymorphic sequence markers were mapped. The maps were aligned by co-dominant or doubly heterozygous dominant anchor markers. Twelve pairs of homologous linkage groups could be integrated into consensus linkage groups. Resistance phenotypes and segregating characteristics were scored as quantitative traits in three or four growing seasons. Interval mapping reproducibly localized genetic factors that correlated with fungal disease resistances to specific regions on three linkage groups of the maternal 'Regent' map. A QTL for resistance to Uncinula necator was identified on linkage group 16, and QTLs for endurance to Plasmopara viticola on linkage groups 9 and 10 of 'Regent'. Additional QTLs for the onset of berry ripening ("veraison"), berry size and axillary shoot growth were identified. Berry color segregated as a simple trait in this cross of two red varieties and was mapped as a morphological marker. Six markers derived from functional genes could be localized. This dissection of polygenic fungus disease resistance in grapevine allows the development of marker-assisted selection for breeding, the characterization of genetic resources and the isolation of the corresponding genes.

Chromosome Mapping↗
PubMed2003

Soybean seed lustre phenotype and surface protein cosegregate and map to linkage group E.

Soybean (Glycine max (L.) Merr.) seeds vary in their surface properties. The lustre, or glossiness, of seeds has been classified into several different phenotypes. Soybean seeds that have a dull lustre or moderate bloom (B) may also have abundant seed surface protein, namely, an abundance of the hydrophobic protein from soybean (HPS). The seed surface protein HPS is an allergen (Gly m 1) that causes asthma in persons allergic to soybean dust. In this study, seed lustre and surface protein content are compared among 71 different soybean cultivars and lines. Dull-seeded phenotypes usually possessed abundant surface protein in comparison to shiny-seeded types, although exceptions were observed. An F2 population of 82 individuals from a cross of OX281 (dull lustre, abundant HPS) and Mukden (shiny lustre, trace amounts of HPS) provided a basis for inheritance studies and genetic mapping analysis. Results indicate that dull seed lustre (B) and surface protein (Hps) loci are dominant Mendelian traits that cosegregate and map to soybean linkage group E. Molecular markers were used to construct a genetic map of 28 cM encompassing B and Hps. Two different molecular markers cosegregated with each of the loci. This study provides additional evidence that Hps may play a role in the adhesion of endocarp tissues to the seed, and offers new methods of selection for seed lustre and surface protein composition in soybean.

Chromosome Mapping↗
PubMed1997

A Bayesian approach to multipoint mapping in nuclear families.

We describe the application of a Markov Chain Monte Carlo approach for multipoint mapping of a quantitative trait locus to the Nuclear Families simulated data. The method involves repeated sampling of genotype vectors for each nuclear family from their conditional distributions, given phenotypes, markers, and model parameters, using peeling and gene dropping, followed by random sampling of each model parameter given genotypes and the other parameters. Reversible jump methods are used to sample the number of trait loci.

Bayes Theorem↗
PubMed2004

[Progress on the sheep genome project].

During the last few years,advances in livestock genome projects have been remarkable. Species-specific genetic maps exist for pig, chicken, cattle, sheep, horse,and deer with marker intervals of 5 to 20 cM. These maps have been essential for the identification of genes and genetic markers associated with importantly economic traits in livestock. In this paper, advances of gene map, comparative map, the genes for importantly economic traits and quantitative trait loci (QTL) mapping were briefly introduced in sheep.

Animals↗
PubMed2000

Annuality, perenniality and cell death.

This essay considers annuality and perenniality as quantitative traits and discusses the application of established and new genetic tools to the analysis of plant life histories. Annual/perennial status is a function of meristem determinacy in combination with the processes of cell death and disposal employed by plants to generate well-adapted anatomies and morphologies. Creeping perennials, like clover or bracken, seem to move around in the environment. They do this by extending into unoccupied space while the oldest tissues behind the growing and mature regions senesce, die and decompose. Trees do essentially the same thing, except that they develop vertically and the old dead tissue does not disappear but instead persists as wood. A root system is a kind of upended vertical perennial. The balance between exploratory growth and the wave of tissue death that succeeds it is a major determinant of perenniality. So although perenniality and annuality may appear to be dramatically different traits, extremes of behaviour can arise by a relatively minor change in the relationship between growth and death. This conclusion is supported by evidence from genome dosage studies, from the practical experiences of breeding perennial-type traits into annual backgrounds and from molecular cladistics. Applications of methods for the genetic analysis of quantitative characters are described, including the exploitation of introgression mapping in Lolium-Festuca and quantitative trait locus mapping in cereals and other species.

Apoptosis↗
PubMed2026

Exploring genomic regions regulating the liver transcriptome and energy homeostasis in pigs.

In pigs, energy homeostasis has an impact on meat quality and health. In a Duroc pig population, 30 quantitative trait locus (QTL) regions associated with fatty acid (FA) composition in adipose tissue, plasma, liver and muscle were previously identified. Mapping of expression quantitative trait locus (eQTL) regions will provide a molecular hypothesis for genotype-phenotype interactions and may allow the identification of shared causal variants, key to increasing our understanding of the genetic regulation of FA composition and energy homeostasis. However, gene expression is impacted by environmental factors, while individual-level allelic imbalance (AI) can be more reliable and can be surveyed via allelic-specific expression (ASE) analysis. Furthermore, treatment of ASE as a quantitative trait allows the identification of allele-specific expression quantitative trait loci (aseQTLs), which are variants whose heterozygosity is linked to the AI of a nearby single-nucleotide polymorphism (SNP), pointing to regulatory elements. In this study, liver was selected as a key metabolic hub with an important role in the regulation of energy homeostasis, and 310 liver RNA sequencing samples were analysed using a combination of (1) eQTL mapping, (2) ASE analysis, and (3) aseQTL mapping methods. A total of 2 188 eQTL regions were identified, mostly cis-eQTL regions (73.17%). ASE analysis reported 1 964 ASE SNPs, associated with 633 genes. Finally, aseQTL mapping reported 64 172 aseQTL, associated with the AI of 31 genes. Colocalisation analysis combined with ASE analysis showed that the expression of FADS1 and FADS2 genes is associated with the polyunsaturated FA composition in several tissues, where microRNA regulation may be present. Finally, in the DGAT2 gene, annotated in a QTL region associated with multiple FAs in adipose tissue, ASE revealed allelic imbalance in the 3' untranslated region (UTR) of this gene. Allelic differential expression can be caused by a 13-bp insertion affecting messenger RNA stability, previously described, exemplifying how allelic imbalance is caused by a post-transcriptional regulatory mechanism undetectable by eQTL mapping. Furthermore, aseQTLs were associated with this gene, linked to a previously identified copy number variant not yet associated with DGAT2 expression. These results demonstrate how ASE analysis and aseQTL mapping can complement eQTL mapping, as they resolved a complex region affected by allelic heterogeneity, a main confounding effect of QTL mapping. In conclusion, the combination of eQTL mapping, ASE analysis and aseQTL mapping allowed the characterisation of the regulation of liver gene expression, improving our understanding of the genetic determinism of energy homeostasis.

Allele-specific expression↗
PubMed2000

Bovine CAPN1 maps to a region of BTA29 containing a quantitative trait locus for meat tenderness.

Micromolar calcium activated neural protease (CAPN1) was investigated as a potential candidate gene for a quantitative trait locus (QTL) on BTA29 affecting meat tenderness. A 2,948-bp bovine cDNA containing the entire coding region of the gene was obtained, showing 91% identity to human CAPN1. The 716 AA protein predicted from this sequence shows 97% similarity (95% identity) to the 714 AA human protein. Analysis of the gene structure revealed that CAPN1 mRNA is encoded by at least 19 exons, and 11,055 bp of the gene were sequenced, including 17 introns. Two single nucleotide polymorphisms (SNP) were detected in intron 12 and were used to map bovine CAPN1 to the telomeric end of the BTA29 linkage group. This approximately coincides with the position of the QTL, demonstrating that CAPN1 protease is a positional candidate gene potentially affecting variation in meat tenderness in a bovine resource mapping population.

Amino Acid Sequence↗
PubMed2004

The effect of an imprecise map on interval mapping QTLs.

The statistical analysis of quantitative trait locus (QTL) experiments relies on the use of a linkage map of the markers genotyped. Such a map is, at best, a good estimate of the true map. Resources might be diverted into developing better marker maps or improved maps become available after the analysis, raising concerns over the original analysis. It is therefore important to understand the sensitivity of QTL analysis to map inaccuracy. We have used simulation methods to investigate the consequences of an incorrect map on the results of a QTL analysis using interval mapping. Backcross data sets were generated with a particular map and then analysed with both the correct map and incorrect maps. If the incorrect maps maintained the true linkage groups (i.e. no markers were incorrectly assigned to another linkage group), the accuracy of the map had little or no impact on the ability to detect QTLs, the true significance levels of the tests or the relative placement of QTLs. When a marker was incorrectly placed on another linkage group, there was a small increase in the level of the test. After adjusting for this increase, there was a decrease in power to detect a QTL near the misplaced marker. This decrease was of a similar magnitude to that found when using a single-marker analysis compared with interval mapping. These results mean that QTL analyses can proceed without the need for very accurate marker maps, and that estimated QTL positions can be translated onto updated maps without the need for reanalysis.

Chromosome Mapping↗
PubMed2005

Genetics and genomics of depression.

Depressive disorders are among the most common psychiatric diseases, with prevalence estimates ranging from 5% to a maximum of 20%. Despite their high prevalence and socioeconomic impact, little is known about their etiology. Heritability estimates demonstrate up to a 50% genetic component based on family aggregation and contrasting monozygotic and dizygotic twin studies. The low relative risk to siblings ( lambda sib <1.5) makes the search for their genetic determinants very tedious. Gene-environment interaction has been recognized for a long time in the pathophysiology of depression, and its best biological substratum at present is represented by the serotonin transporter (5-HTT) gene, where several copies of its short allele culminate in depression and suicide in response to lifelong stress events. Many total genome scans have been performed with variable results, the most authoritative being the one of Utah pedigrees with a strong family history of major depression. It identified a locus on chromosome 12 encompassing a gene cluster and sex-specific predisposition. Nevertheless, recent genome scan meta-analysis yielded somewhat disappointing conclusions with a relatively low significance for quantitative trait loci on chromosomes 9, 10, 14, and 18. Studies on animal models have contributed to the chromosomal mapping of many behavioral traits, including anxiety, the stress response, and depression. Although F2 crosses constitute a classical approach, novel models of recombinant inbred strain and recombinant congenic strain animals allow for a rapid initial localization of any traits. This type of analysis has led us to uncover significant loci for the stress response and anxiety in rats and mice.

Animals↗
PubMed2000

Developing expressed sequence tags (ESTs) from polymorphic transcript-derived fragments (TDFs) in cassava (Manihot esculenta Crantz).

We applied the cDNA-AFLP (amplified fragment length polymorphism) technique to mRNA from the parents of a cassava (Manihot esculenta) genetic mapping population, and obtained more than 500 transcript-derived fragments (TDFs) that were unique in either parent. A subset of 50 TDFs were cloned and sequenced. Sequence alignment of the expressed sequence tags (ESTs) revealed mostly genes of unknown function. Six of the TDFs were mapped on to the cassava genetic map. We also demonstrated by genetic mapping of the TDFs, as RFLP (restriction fragment length polymorphism) markers, that TDFs are more polymorphic than random cDNAs. Generation of ESTs as differentially expressed sequences, in time or between different varieties, is proposed as a way of developing ESTs around specific traits for the candidate locus approach to mapping complex traits.

Chromosome Mapping↗
PubMed2004

Determination of PRKAG1 coding sequence and mapping of PRKAG1 and PRKAG2 relatively to porcine back fat thickness QTL.

PRKAG1, PRKAG2 and PRKAG3 encode three isoforms of AMP-activated protein kinase gamma chain. A major effect on meat quality and a medium effect on back fat thickness of the RN- mutation in the PRKAG3 gene has previously been reported. We have now mapped PRKAG1 and PRKAG2 at expected locations on SSC5 and SSC18 by analysis of radiation hybrids (IMpRH panel). PRKAG2 has been mapped in a region where no quantitative trait loci (QTL) has been reported. PRKAG1 has been mapped close to (but probably outside) a region containing a QTL influencing fatness traits. We have determined the full coding sequence of PRKAG1. No missense mutation was identified when comparing the coding sequence of one Meishan and one Large White boars. Further work is, however, required to determine if a polymorphism in PRKAG1 could be responsible for a part of the variability observed on fatness traits.

Adipose Tissue↗
PubMed2004

Simultaneous mapping of epistatic QTL in chickens reveals clusters of QTL pairs with similar genetic effects on growth.

We used simultaneous mapping of interacting quantitative trait locus (QTL) pairs to study various growth traits in a chicken F2 intercross. The method was shown to increase the number of detected QTLs by 30 % compared with a traditional method detecting QTLs by their marginal genetic effects. Epistasis was shown to be an important contributor to the genetic variance of growth, with the largest impact on early growth (before 6 weeks of age). There is also evidence for a discrete set of interacting loci involved in early growth, supporting the previous findings of different genetic regulation of early and late growth in chicken. The genotype-phenotype relationship was evaluated for all interacting QTL pairs and 17 of the 21 evaluated QTL pairs could be assigned to one of four clusters in which the pairs in a cluster have very similar genetic effects on growth. The genetic effects of the pairs indicate commonly occurring dominance-by-dominance, heterosis and multiplicative interactions. The results from this study clearly illustrate the increase in power obtained by using this novel method for simultaneous detection of epistatic QTL, and also how visualization of genotype-phenotype relationships for epistatic QTL pairs provides new insights to biological mechanisms underlying complex traits.

Algorithms↗
PubMed1989

Gene amplification associated with the dominant cob-354 cobalt resistance trait in Dictyostelium discoideum.

A DNA amplification is correlated with the dominant, unstable cob-354 cobalt resistance trait in the cellular slime mold, Dictyostelium discoideum. The amplified DNA is present as about 50 copies of an extrachromosomal element. Cells grown under nonselective conditions in the absence of cobalt ions lose both the cobalt resistance trait and all extrachromosomal copies of the amplified DNA. The amplified DNA is transferrable to new genetic backgrounds by parasexual genetic crosses. These results explain the inability to map the cob-354 trait to a linkage group. The chromosomal origin of the amplified DNA is group III or VI. Thus the resistance trait appears to be independent of the previously known cobalt resistance locus, cobA, which maps to group VII. A developmental defect involving the production of multiply-tipped aggregates that do not complete fruiting body formation also is correlated with the presence of the amplified DNA.

Animals↗