The first decision made by an angiosperm seed, whether to germinate or not, is based on integration of various environmental signals such as water and light. The phytochromes (Phys) act as red and far-red light (Pfr) photoreceptors to mediate light signaling through yet uncharacterized pathways. We report here that the PIF3-like 5 (PIL5) protein, a basic helix-loop-helix transcription factor, is a key negative regulator of phytochrome-mediated seed germination. PIL5 preferentially interacts with the Pfr forms of Phytochrome A (PhyA) and Phytochrome B (PhyB). Analyses of a pil5 mutant in conjunction with phyA and phyB mutants, a pif3 pil5 double mutant, and PIL5 overexpression lines indicate that PIL5 is a negative factor in Phy-mediated promotion of seed germination, inhibition of hypocotyl negative gravitropism, and inhibition of hypocotyl elongation. Our data identify PIL5 as the first Phy-interacting protein that regulates seed germination.

Rheumatoid arthritis (RA) is a common autoimmune disease with a complex genetic etiology. Herein we identify a single-nucleotide polymorphism (SNP) in the promoter region of FcRH3, a member of the Fc receptor homolog family, that is associated with RA susceptibility (OR=2. 15, P=0.00000085). This polymorphism alters the binding affinity of nuclear factor-κB and regulates NIH-PA Author ManuscriptNIH-PA Author Manuscript NIH-PA Author ManuscriptFcRH3 expression. High FcRH3 expression on B-cells and augmented autoantibody production were observed in individuals with the disease-susceptible genotype. Associations were also found between the SNP and susceptibility to autoimmune thyroid disease and systemic lupus erythematosus. FcRH3 may thus play a pivotal role in autoimmunity.Rheumatoid arthritis represents one of the most common autoimmune diseases, and is characterized by inflammation of synovial tissue and joint destruction. Although the disease is believed to result from a combination of genetic and environmental factors, the complete etiology of RA has not yet been clarified 1 . While specific haplotypes of human leukocyte antigen (HLA)-DRB1, usually referred to as shared-epitope (SE) sequences 2 , have been repeatedly reported as conferring RA-susceptibility 3,4 , other genetic components are also involved in the pathogenesis of RA 5 . This combination of HLA haplotypes and non-HLA genes accounting for disease susceptibility is also seen in other autoimmune diseases 6-8 . In autoimmune thyroid disease (AITD), for instance, studies have consistently shown that the HLA-DR3 haplotype is associated with disease risk, in addition to a functional haplotype of a non-HLA gene, CTLA4, that has recently been associated with AITD susceptibility 9 .Identification of non-HLA genes associated with RA susceptibility and other autoimmunities seems difficult, due to the low relative risk of disease resulting from these non-HLA genes compared with the strong relative risk from disease-associated HLA haplotypes. In a search for non-HLA determinants of disease susceptibility, whole genome studies have been conducted for both human autoimmune diseases and experimental animal models. These studies have revealed non-random clustering of susceptibility loci for clinically distinct diseases 8,10 . This overlapping of susceptibility loci for multiple autoimmunities suggests the existence of common susceptibility genes in those regions. Intense studies of loci-clustering regions has revealed genes commonly associated with multiple autoimmune diseases, such as CTLA4 on 2q33 (ref. and Idd17 (ref. 25)). Although 1q21-23 is a strong candidate region for RA susceptible genes, as above mentioned, the association of classical FcγRs with disease susceptibility remains controvertial 26,27 . The present study focused on the 1q21-23 region to identify RA-associated genes in Japanese subjects using linkage disequilibrium (LD) mapping. RESULTS Case-control study by SNP-based LD-mapping in 1q21-23To evaluate the extent of association, we a...

Attention deficit hyperactivity disorder (ADHD) is a psychiatric disorder that affects ~5% of school-aged children; however, the mechanisms underlying ADHD remain largely unclear. Here we report a previously unidentified association between G protein-coupled receptor kinase-interacting protein-1 (GIT1) and ADHD in humans. An intronic single-nucleotide polymorphism in GIT1, the minor allele of which causes reduced GIT1 expression, shows a strong association with ADHD susceptibility in humans. Git1-deficient mice show ADHD-like phenotypes, with traits including hyperactivity, enhanced electroencephalogram theta rhythms and impaired learning and memory. Hyperactivity in Git1(-/-) mice is reversed by amphetamine and methylphenidate, psychostimulants commonly used to treat ADHD. In addition, amphetamine normalizes enhanced theta rhythms and impaired memory. GIT1 deficiency in mice leads to decreases in ras-related C3 botulinum toxin substrate-1 (RAC1) signaling and inhibitory presynaptic input; furthermore, it shifts the neuronal excitation-inhibition balance in postsynaptic neurons toward excitation. Our study identifies a previously unknown involvement of GIT1 in human ADHD and shows that GIT1 deficiency in mice causes psychostimulant-responsive ADHD-like phenotypes.

Objective. Anticitrullinating autoantibodies are specific markers for rheumatoid arthritis (RA). A functional haplotype of 4 exonic single-nucleotide polymorphisms (SNPs) in a citrullinating enzyme, peptidylarginine deiminase 4 (PADI4), was shown to be associated with susceptibility to RA in a Japanese population and was shown to increase the stability of PADI4 messenger RNA. However, the association was not confirmed in 4 subsequent studies involving Caucasian RA patients living in the UK, a French Caucasian population, and a Spanish population. The aim of the current study was to investigate the association of SNPs in the PADI4 gene with RA in a Korean population.Methods. Four exonic SNPs of the PADI4 gene (padi4_89, padi4_90, padi4_92, and padi4_104) were genotyped in 545 unrelated patients with RA and 392 controls, using the MassArray SNP genotyping system. Allelic, genotypic, and haplotypic associations of the SNPs with RA susceptibility were examined using the chi-square test and multivariate logistic regression analyses.Results. Increased RA susceptibility was significantly associated with the minor alleles of padi4_89 (P ‫؍‬ 2.3 ؋ 10 ؊5 ), padi4_90 (P ‫؍‬ 2.3 ؋ 10 ؊5 ), padi4_92 (P ‫؍‬ 2.1 ؋ 10 ؊5 ), and padi4_104 (P ‫؍‬ 1.1 ؋ 10 ؊3 ) and the haplotype carrying the 4 minor alleles (P ‫؍‬ 1.0 ؋ 10 ؊4 ). Genotypes carrying the minor alleles and HLA-DRB1 shared epitope (SE) alleles (P ‫؍‬ 9.4 ؋ 10 ؊21 ) were also associated with increased RA susceptibility. The genotypic associations were sustained among individuals who did not carry any SE alleles, except in the case of padi4_104. Individuals carrying the risk SNPs and/or SE alleles were more susceptible to RA than were individuals carrying neither risk SNPs nor SE alleles.Conclusion. The PADI4 SNPs and haplotypes are associated with RA susceptibility in Koreans. Thus, the association of PADI4 with RA may depend on genetic heterogeneity between Asians and Europeans.

We propose a novel, efficient and intuitive approach of estimating mRNA abundances from the whole transcriptome shotgun sequencing (RNA-Seq) data. Our method, NEUMA (Normalization by Expected Uniquely Mappable Area), is based on effective length normalization using uniquely mappable areas of gene and mRNA isoform models. Using the known transcriptome sequence model such as RefSeq, NEUMA pre-computes the numbers of all possible gene-wise and isoform-wise informative reads: the former being sequences mapped to all mRNA isoforms of a single gene exclusively and the latter uniquely mapped to a single mRNA isoform. The results are used to estimate the effective length of genes and transcripts, taking experimental distributions of fragment size into consideration. Quantitative RT–PCR based on 27 randomly selected genes in two human cell lines and computer simulation experiments demonstrated superior accuracy of NEUMA over other recently developed methods. NEUMA covers a large proportion of genes and mRNA isoforms and offers a measure of consistency (‘consistency coefficient’) for each gene between an independently measured gene-wise level and the sum of the isoform levels. NEUMA is applicable to both paired-end and single-end RNA-Seq data. We propose that NEUMA could make a standard method in quantifying gene transcript levels from RNA-Seq data.