TASK DEFINITION: In this task, you are given an abstract of article. Your task is to generate title for this article. Preferred titles are under thirty words.
PROBLEM: An adoption study of genetic effects on obesity in adulthood was carried out in which adoptees separated from their natural parents very early in life were compared with their biological full and half siblings reared by their natural parents. The adoptees represented four groups who by sampling from a larger population were categorised as either thin, medium weight, overweight, or obese. Weight and height were obtained for 115 full siblings of 57 adoptees and for 850 half siblings of 341 adoptees. In full siblings body mass index (kg/m2) significantly increased with weight of the adoptees. Body mass index of the half siblings showed a steady but weaker increase across the four weight groups of adoptees. There were no significant interactions with sex of the adoptees, sex of the siblings, or (for the half siblings) sex of the common parent. In contrast with the findings in half siblings and (previously) the natural parents there was a striking, significant increase in body mass index between full siblings of overweight and obese adoptees. The degree of fatness in adults living in the same environment appears to be influenced by genetic factors independent of sex, which may include polygenic as well as major gene effects on obesity.

SOLUTION: Genetics of obesity in adult adoptees and their biological siblings.

PROBLEM: Unilateral injection of kainic acid (KA) into the dorsal hippocampus of adult mice induces spontaneous recurrent partial seizures and replicates histopathological changes observed in human mesial temporal lobe epilepsy (MTLE) (Bouilleret V et al., Neuroscience 1999; 89:717-729). Alterations in pre- and postsynaptic components of GABAergic neurotransmission were investigated immunohistochemically at different time points (1-120 days) in this mouse model of MTLE. Markers of GABAergic interneurons (parvalbumin, calbindin-D28k, and calretinin), the type-1 GABA transporter (GAT1), and major GABA(A)-receptor subunits expressed in the hippocampal formation were analyzed. Acutely, KA injection produced a profound loss of hilar cells but only limited damage to CA1 and CA3 pyramidal cells. In addition, parvalbumin and calbindin-D28k staining of interneurons disappeared irreversibly in CA1 and dentate gyrus (DG), whereas calretinin staining was spared. The prominent GABA(A)-receptor alpha1 subunit staining of interneurons also disappeared after KA treatment, suggesting acute degeneration of these cells. Likewise, GAT1 immunoreactivity revealed degenerating terminals at 24 h post-KA in CA1 and DC and subsided almost completely thereafter. Loss of CA1 and, to a lesser extent, CA3 neurons became evident at 7-15 days post-KA. It was more accentuated after 1 month, accompanied by a corresponding reduction of GABA(A)-receptor staining. In contrast, DC granule cells were markedly enlarged and dispersed in the molecular layer and exhibited a prominent increase in GABA(A)-receptor subunit staining. After 4 months, the dorsal CA1 area was lost almost entirely, CA3 was reduced, and the DG represented most of the remaining dorsal hippocampal formation. No significant morphological alterations were detected contralaterally. These results suggest that loss of hilar cells and GABAergic neurons contributes to epileptogenesis in this model of MTLE. In contrast, long-term degeneration of pyramidal cells and granule cell dispersion may reflect distinct responses to recurrent seizures. Finally, GABA(A)-receptor upregulation in the DG may represent a compensatory response persisting for several months in epileptic mice.

SOLUTION: Early loss of interneurons and delayed subunit-specific changes in GABA(A)-receptor expression in a mouse model of mesial temporal lobe epilepsy.

PROBLEM: Expression quantitative trait loci (eQTL) mapping aims to determine genomic regions that regulate gene transcription. Expression QTL is used to study the regulatory structure of normal tissues and to search for genetic factors in complex diseases such as cancer, diabetes, and cystic fibrosis. A modern eQTL dataset contains millions of SNPs and thousands of transcripts measured for hundreds of samples. This makes the analysis computationally complex as it involves independent testing for association for every transcript-SNP pair. The heavy computational burden makes eQTL analysis less popular, often forces analysts to restrict their attention to just a subset of transcripts and SNPs. As larger genotype and gene expression datasets become available, the demand for fast tools for eQTL analysis increases. We present a new method for fast eQTL analysis via linear models, called Matrix eQTL. Matrix eQTL can model and test for association using both linear regression and ANOVA models. The models can include covariates to account for such factors as population structure, gender, and clinical variables. It also supports testing of heteroscedastic models and models with correlated errors. In our experiment on large datasets Matrix eQTL was thousands of times faster than the existing popular software for QTL/eQTL analysis. Matrix eQTL is implemented as both Matlab and R packages and thus can easily be run on Windows, Mac OS, and Linux systems. The software is freely available at the following address: http://www.bios.unc.edu/research/genomic_software/Matrix_eQTL

SOLUTION:
Matrix eQTL: Ultra fast eQTL analysis via large matrix operations