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Leopard complex spotting is a group of white spotting patterns in horses caused by an incompletely dominant gene (LP) where homozygotes (LP/LP) are also affected with congenital stationary night blindness. Previous studies implicated Transient Receptor Potential Cation Channel, Subfamily M, Member 1 (TRPM1) as the best candidate gene for both CSNB and LP. RNA-Seq data pinpointed a 1378 bp insertion in intron 1 of TRPM1 as the potential cause. This insertion, a long terminal repeat (LTR) of an endogenous retrovirus, was completely associated with LP, testing 511 horses (χ(2)=1022.00, p<

The basidiomycete isolate b19, originally identified by morphological characteristics of the fruiting body as Nematoloma frowardii, efficiently produces manganese peroxidase (MNP) and is used for degradation of natural, persistent aromatic polymers (lignin, humic acids and brown coal components). The N. frowardii MNP has shown good activity in conversion of xenobiotic compounds such as polycyclic hydrocarbons and trinitrotoluene. However, this biotechnologically promising fungus has not previously been studied at the molecular biology level. We show here that according to the molecular characterization of its main MNP isozyme, Nf b19 MNP2, and partial sequencing of its MNP3-, three lignin peroxidase- and two laccase-encoding genes, and the gene encoding the ribosomal SSU 18S RNA, that the fungus has a close phylogenetic relationship to the white-rot basidiomycete Phlebia radiata (Fr.). Ribosomal internal transcribed spacer (ITS) sequence (ITS1 +5.8S+ITS2) phylogeny reclassifies Nf b19 as a possible representative of a new species of the genus Phlebia, nearest to the Phlebia acerina clade. The genus Phlebia belongs to a completely different family (Corticiaceae) and order (Aphyllophorales) within the phylum Basidiomycota than the genus Nematoloma, which is classified in the order Agaricales, family Strophariaceae. Our results thus indicate a need for systematic re-identification of the previously named N. frowardii isolate b19.

Abstract Background This study focused on the dynamics of genome-wide effects on five milk production and eight fertility traits as well as genetic correlations between the traits. For 2,405 Holstein Friesian bulls, estimated breeding values (EBVs) were used. The production traits were additionally assessed in 10-day intervals over the first 60 lactation days, as this stage is physiologically the most crucial time in milk production. Results SNPs significantly affecting the EBVs of the production traits could be separated into three groups according to the development of the size of allele effects over time: 1) increasing effects for all traits; 2) decreasing effects for all traits; and 3) increasing effects for all traits except fat yield. Most of the significant markers were found within 22 haplotypes spanning on average 135,338 bp. The DGAT1 region showed high density of significant markers, and thus, haplotype blocks. Further functional candidate genes are proposed for haplotype blocks of significant SNPs (KLHL8, SICLEC12, AGPAT6 and NID1). Negative genetic correlations were found between yield and fertility traits, whilst content traits showed positive correlations with some fertility traits. Genetic correlations became stronger with progressing lactation. When correlations were estimated within genotype classes, correlations were on average 0.1 units weaker between production and fertility traits when the yield increasing allele was present in the genotype. Conclusions This study provides insight into the expression of genetic effects during early lactation and suggests possible biological explanations for the presented time-dependent effects. Even though only three markers were found with effects on fertility, the direction of genetic correlations within genotype classes between production and fertility traits suggests that alleles increasing the milk production do not affect fertility in a more negative way compared to the decreasing allele.

Abstract Background High density genotyping arrays have become established as a valuable research tool in human genetics. Currently, more than 300 genome wide association studies were published for human reporting about 1,000 SNPs that are associated with a phenotype. Also in animal sciences high density genotyping arrays are harnessed to analyse genetic variation. To exploit the full potential of this technology single nucleotide polymorphisms (SNPs) on the chips should be well characterized and their chromosomal position should be precisely known. This, however, is a challenge if the genome sequence is still subject to changes. Results We have developed a mapping strategy and a suite of software scripts to update the chromosomal positions of oligomer sequences used for SNP genotyping on high density arrays. We describe the mapping procedure in detail so that scientists with moderate bioinformatics skills can reproduce it. We furthermore present a case study in which we re-mapped 54,001 oligomer sequences from Ilumina's BovineSNP50 beadchip to the bovine genome sequence. We found in 992 cases substantial discrepancies between the manufacturer's annotations and our results. The software scripts in the Perl and R programming languages are provided as supplements. Conclusions The positions of oligomer sequences in the genome are volatile even within one build of the genome. To facilitate the analysis of data from a GWAS or from an expression study, especially with species whose genome assembly is still unstable, it is recommended to update the oligomer positions before data analysis.

Abstract Background The splicing of pre-mRNAs is conspicuously often variable and produces multiple alternatively spliced (AS) isoforms that encode different messages from one gene locus. Computational studies uncovered a class of highly similar isoforms, which were related to tandem 5'-splice sites (5'ss) and 3'-splice sites (3'ss), yet with very sparse anecdotal evidence in experimental studies. To compare the types and levels of alternative tandem splice site exons occurring in different human organ systems and cell types, and to study known sequence features involved in the recognition and distinction of neighboring splice sites, we performed large-scale, stringent alignments of cDNA sequences and ESTs to the human and mouse genomes, followed by experimental validation. Results We analyzed alternative 5'ss exons (A5Es) and alternative 3'ss exons (A3Es), derived from transcript sequences that were aligned to assembled genome sequences to infer patterns of AS occurring in several thousands of genes. Comparing the levels of overlapping (tandem) and non-overlapping (competitive) A5Es and A3Es, a clear preference of isoforms was seen for tandem acceptors and donors, with four nucleotides and three to six nucleotides long exon extensions, respectively. A subset of inferred A5E tandem exons was selected and experimentally validated. With the focus on A5Es, we investigated their transcript coverage, sequence conservation and base-paring to U1 snRNA, proximal and distal splice site classification, candidate motifs for cis-regulatory activity, and compared A5Es with A3Es, constitutive and pseudo-exons, in H. sapiens and M. musculus. The results reveal a small but authentic enriched set of tandem splice site preference, with specific distances between proximal and distal 5'ss (3'ss), which showed a marked dichotomy between the levels of in- and out-of-frame splicing for A5Es and A3Es, respectively, identified a number of candidate NMD targets, and allowed a rough estimation of a number of undetected tandem donors based on splice site information. Conclusion This comparative study distinguishes tandem 5'ss and 3'ss, with three to six nucleotides long extensions, as having unusually high proportions of AS, experimentally validates tandem donors in a panel of different human tissues, highlights the dichotomy in the types of AS occurring at tandem splice sites, and elucidates that human alternative exons spliced at overlapping 5'ss posses features of typical splice variants that could well be beneficial for the cell.

Advanced intercross lines (AIL) have proven to be a powerful tool in genetic research to map complex genetic traits. The advantage of AIL is the high enrichment of visible recombination events to fine map the position of the target gene. Therefore, AIL are generated under the avoidance of inbreeding. We developed an online software tool, R andoM ate, that generates random mating schemes such that only animals from different families are paired. When animals have to be selected randomly for mating, R andoM ate optimizes the mating scheme such that all families contribute equally to the next generation. R andoM ate uses a divide-and-conquer algorithm to define a mating scheme without brother-sister matings for all animals of a generation. If not all animals can be considered for the next generation, the mating scheme maximizes the randomness of the occurrences of animals from their families to make the family contributions as equal as possible. R andoM ate is freely available at . [ABSTRACT FROM AUTHOR]

Leopard complex spotting is a group of white spotting patterns in horses caused by an incompletely dominant gene (LP) where homozygotes (LP/LP) are also affected with congenital stationary night blindness. Previous studies implicated Transient Receptor Potential Cation Channel, Subfamily M, Member 1 (TRPM1) as the best candidate gene for both CSNB and LP. RNA-Seq data pinpointed a 1378 bp insertion in intron 1 of TRPM1 as the potential cause. This insertion, a long terminal repeat (LTR) of an endogenous retrovirus, was completely associated with LP, testing 511 horses (χ2=1022.00, p<<0.0005), and CSNB, testing 43 horses (χ2=43, p<<0.0005). The LTR was shown to disrupt TRPM1 transcription by premature poly-adenylation. Furthermore, while deleterious transposable element insertions should be quickly selected against the identification of this insertion in three ancient DNA samples suggests it has been maintained in the horse gene pool for at least 17,000 years. This study represents the first description of an LTR insertion being associated with both a pigmentation phenotype and an eye disorder. [ABSTRACT FROM AUTHOR]

Recent technological progress has permitted the efficient performance of genome-wide association studies (GWAS) to map genetic variants associated with common diseases. Here, we analyzed 2,893 single nucleotide polymorphisms (SNPs) that have been identified in 593 published GWAS as associated with a disease phenotype with respect to their genomic location. In absolute numbers, most significant SNPs are located in intergenic regions and introns. When compared to their representation on the chips, there is essentially overrepresentation of nonsynonymous coding SNPs (nsSNPs), synonymous coding SNPs, and SNPs in untranscribed regions upstream of genes among the disease associated SNPs. A Gene Ontology term analysis showed that genes putatively causing a phenotype often code for membrane associated proteins or signal transduction genes.

Spliceosomes are macro-complexes involving hundreds of proteins with many functional interactions. Spliceosome assembly belongs to the key processes that enable splicing of mRNA and modulate alternative splicing. A detailed list of factors involved in spliceosomal reactions has been assorted over the past decade, but, their functional interplay is often unknown and most of the present biological models cover only parts of the complete assembly process. It is a challenging task to build a computational model that integrates dispersed knowledge and combines a multitude of reaction schemes proposed earlier. Because for most reactions involved in spliceosome assembly kinetic parameters are not available, we propose a discrete modeling using Petri nets, through which we are enabled to get insights into the system's behavior via computation of structural and dynamic properties. In this paper, we compile and examine reactions from experimental reports that contribute to a functional spliceosome. All these reactions form a network, which describes the inventory and conditions necessary to perform the splicing process. The analysis is mainly based on system invariants. Transition invariants (T-invariants) can be interpreted as signaling routes through the network. Due to the huge number of T-invariants that arise with increasing network size and complexity, maximal common transition sets (MCTS) and T-clusters were used for further analysis. Additionally, we introduce a false color map representation, which allows a quick survey of network modules and the visual detection of single reactions or reaction sequences, which participate in more than one signaling route. We designed a structured model of spliceosome assembly, which combines the demands on a platform that i) can display involved factors and concurrent processes, ii) offers the possibility to run computational methods for knowledge extraction, and iii) is successively extendable as new insights into spliceosome function are reported by experimental reports. The network consists of 161 transitions (reactions) and 140 places (reactants). All reactions are part of at least one of the 71 T-invariants. These T-invariants define pathways, which are in good agreement with the current knowledge and known hypotheses on reaction sequences during spliceosome assembly, hence contributing to a functional spliceosome. We demonstrate that present knowledge, in particular of the initial part of the assembly process, describes parallelism and interaction of signaling routes, which indicate functional redundancy and reflect the dependency of spliceosome assembly initiation on different cellular conditions. The complexity of the network is further increased by two switches, which introduce alternative routes during A-complex formation in early spliceosome assembly and upon transition from the B-complex to the C-complex. By compiling known reactions into a complete network, the combinatorial nature of invariant computation leads to pathways that have previously not been described as connected routes, although their constituents were known. T-clusters divide the network into modules, which we interpret as building blocks in spliceosome maturation. We conclude that Petri net representations of large biological networks and system invariants, are well-suited as a means for validating the integration of experimental knowledge into a consistent model. Based on this network model, the design of further experiments is facilitated.