Multilocus tetrasomic linkage analysis using hidden Markov chain model.

The availability of reliable genetic linkage maps is crucial for functional and evolutionary genomic analyses. Established theory and methods of genetic linkage analysis have made map construction a routine exercise in diploids. However, many evolutionarily, ecologically, and/or agronomically important species are autopolyploids, with autotetraploidy being a typical example.

[The transcriptome analysis of barley (Hordeum vulgare L.) using the Affymetrix Barley1 GeneChip].

An alternative to complete genome sequencing is development and analysis of ESTs-fragments of transcribed coding DNA sequences. The EST collections also enhanced the development of cDNA microarray technologies, which make possible assessing the transcription levels of several thousand genes in a studied tissue of an organism in the same experiment. This paper provides an overview of the results of experiments with a barley microarray, Affymetrix Barley1 GeneChip.

Transcript profiling and expression level mapping.

Transcript abundance data from cRNA hybridizations to Affymetrix microarrays can potentially be used to identify genetic markers to facilitate high-throughput genotyping. We have shown that it is easily possible to use the information from Affymetrix expression arrays to accurately identify over 4,000 robust polymorphic transcript-derived markers (TDMs). We developed the method to identity TDM polymorphisms from experiments involving two tissues in two commercial varieties of barley and their doubled-haploid progeny.

Robust detection and genotyping of single feature polymorphisms from gene expression data.

It is well known that Affymetrix microarrays are widely used to predict genome-wide gene expression and genome-wide genetic polymorphisms from RNA and genomic DNA hybridization experiments, respectively. It has recently been proposed to integrate the two predictions by use of RNA microarray data only. Although the ability to detect single feature polymorphisms (SFPs) from RNA microarray data has many practical implications for genome study in both sequenced and unsequenced species, it raises enormous challenges for statistical modelling and analysis of microarray gene expression data for this objective.

Towards systems genetic analyses in barley: Integration of phenotypic, expression and genotype data into GeneNetwork.

Background: A typical genetical genomics experiment results in four separate data sets; genotype, gene expression, higher-order phenotypic data and metadata that describe the protocols, processing and the array platform. Used in concert, these data sets provide the opportunity to perform genetic analysis at a systems level. Their predictive power is largely determined by the gene expression dataset where tens of millions of data points can be generated using currently available mRNA profiling technologies.

A and C genome distinction and chromosome identification in brassica napus by sequential fluorescence in situ hybridization and genomic in situ hybridization.

The two genomes (A and C) of the allopolyploid Brassica napus have been clearly distinguished using genomic in situ hybridization (GISH) despite the fact that the two extant diploids, B. rapa (A, n = 10) and B. oleracea (C, n = 9), representing the progenitor genomes, are closely related.

Methods for evaluating gene expression from Affymetrix microarray datasets.

Background: Affymetrix high density oligonucleotide expression arrays are widely used across all fields of biological research for measuring genome-wide gene expression. An important step in processing oligonucleotide microarray data is to produce a single value for the gene expression level of an RNA transcript using one of a growing number of statistical methods. The challenge for the researcher is to decide on the most appropriate method to use to address a specific biological question with a given dataset.

Exploiting regulatory variation to identify genes underlying quantitative resistance to the wheat stem rust pathogen Puccinia graminis f. sp. tritici in barley.

We previously mapped mRNA transcript abundance traits (expression-QTL or eQTL) using the Barley1 Affymetrix array and 'whole plant' tissue from 139 progeny of the Steptoe x Morex (St/Mx) reference barley mapping population. Of the 22,840 probesets (genes) on the array, 15,987 reported transcript abundance signals that were suitable for eQTL analysis, and this revealed a genome-wide distribution of 23,738 significant eQTLs. Here we have explored the potential of using these mRNA abundance eQTL traits as surrogates for the identification of candidate genes underlying the interaction between barley and the wheat stem rust fungus Puccinia graminis f.

The role of cis-regulatory motifs and genetical control of expression in the divergence of yeast duplicate genes.

Expression divergence of duplicate genes is widely believed to be important for their retention and evolution of new function, although the mechanism that determines their expression divergence remains unclear. We use a genetical genomics approach to explore divergence in genetical control of yeast duplicate genes created by a whole-genome duplication that occurred about 100 MYA and those with a younger duplication age. The analysis reveals that duplicate genes have a significantly higher probability of sharing common genetic control than pairs of singleton genes.

Identification and characterization of QTL controlling Agrobacterium-mediated transient and stable transformation of Brassica oleracea.

A commonly encountered difficulty with the genetic engineering of crop plants is that different varieties of a particular species can show great variability in the efficiency with which they can be transformed. This increases the effort required to introduce transgenes into particular genetic backgrounds. The use of Substitution Lines has allowed the finer mapping of three Quantitative Trait Loci (tf1, tf2 and tf3) that explain 26% of the variation in the efficiency of Agrobacterium-mediated transformation in Brassica oleracea.

Relevance of connexin deafness (DFNB1) to human evolution.

The connexins are the subunits of a family of proteins that form gap junctions, allowing ions and small molecules to move between adjacent cells. At least four connexins are expressed in the ear, and, although there are known mutations at >100 loci that can cause deafness, those involving DFNB1, in the interval 13q11-q12 containing the GJB2 and GJB6 genes coding for connexins 26 and 30, are the most frequent cause of recessive deafness in many populations. We have suggested that the combined effects of relaxed selection and linguistic homogamy can explain the high frequency of connexin deafness and may have doubled its incidence in this country during the past 200 years.

Integration of the cytogenetic and genetic linkage maps of Brassica oleracea.

We have assigned all nine linkage groups of a Brassica oleracea genetic map to each of the nine chromosomes of the karyotype derived from mitotic metaphase spreads of the B. oleracea var. alboglabra line A12DHd using FISH.