Seoae Cho

Auxin stimulates DWARF4 expression and brassinosteroid biosynthesis in Arabidopsis

Brassinosteroids (BRs) are growth-promoting steroidal hormones. Despite the importance of BRs in plant biology, the signal that initiates BR biosynthesis remains unknown. Among the enzymes involved in BR biosynthesis in Arabidopsis (Arabidopsis thaliana), DWARF4 catalyzes the rate-determining step. Through both the histochemical analysis of DWF4pro:GUS plants and the direct measurement of endogenous BR content, we discovered that BR biosynthesis is stimulated by auxin. When DWF4pro:GUS was subjected to auxin dose-response tests and a time-course analysis, GUS activity started to increase at an auxin concentration of 10 nm, rising noticeably after 1 h of auxin treatment. In addition, the analysis of the DWF4pro:GUS line in BR- and auxin-mutant backgrounds revealed that the induction by auxin requires auxin-signaling pathways but not BRs, which implies that auxin signaling directly controls BR biosynthesis. Furthermore, chromatin immunoprecipitation assays confirmed that auxin inhibits the binding of the transcriptional repressor, BZR1, to the DWF4 promoter. A microarray analysis that was designed to examine the transcriptomes after treatment with auxin alone or auxin plus brassinazole (a BR biosynthetic inhibitor) revealed that genes previously characterized as being auxin responsive are not properly regulated when BR biosynthesis is disrupted by brassinazole. Therefore, our results support the idea that auxin regulates BR biosynthesis, and that auxin thus relies on synthesized BRs for some of its growth-promoting effects in Arabidopsis.

Joint identification of multiple genetic variants via elastic-net variable selection in a genome-wide association analysis.

Unraveling the genetic background of common complex traits is a major goal in modern genetics. In recent years, genome‐wide association (GWA) studies have been conducted with large‐scale data sets of genetic variants. Most of those studies have relied on single‐marker approaches that identify single genetic factors individually and can be limited in considering fully the joint effects of multiple genetic factors on complex traits. Joint identification of multiple genetic factors would be more powerful and would provide better prediction on complex traits since it utilizes combined information across variants. Here we propose a multi‐stage approach for GWA analysis: (1) prescreening, (2) joint identification of putative SNPs based on elastic‐net variable selection, and (3) empirical replication using bootstrap samples. Our approach enables an efficient joint search for genetic associations in GWA analysis. The suggested empirical replication method can be beneficial in GWA studies because one can avoid a costly, independent replication study while eliminating false‐positive associations and focusing on a smaller number of replicable variants. We applied the proposed approach to a GWA analysis, and jointly identified 129 genetic variants having an association with adult height in a Korean population.

Ubiquitous Polygenicity of Human Complex Traits: Genome-Wide Analysis of 49 Traits in Koreans

Recent studies in population of European ancestry have shown that 30%∼50% of heritability for human complex traits such as height and body mass index, and common diseases such as schizophrenia and rheumatoid arthritis, can be captured by common SNPs and that genetic variation attributed to chromosomes are in proportion to their length. Using genome-wide estimation and partitioning approaches, we analysed 49 human quantitative traits, many of which are relevant to human diseases, in 7,170 unrelated Korean individuals genotyped on 326,262 SNPs. For 43 of the 49 traits, we estimated a nominally significant (P<0.05) proportion of variance explained by all SNPs on the Affymetrix 5.0 genotyping array (). On average across 47 of the 49 traits for which the estimate of is non-zero, common SNPs explain approximately one-third (range of 7.8% to 76.8%) of narrow sense heritability. The estimate of is highly correlated with the proportion of SNPs with association P<0.031 (r 2 = 0.92). Longer genomic segments tend to explain more phenotypic variation, with a correlation of 0.78 between the estimate of variance explained by individual chromosomes and their physical length, and 1% of the genome explains approximately 1% of the genetic variance. Despite the fact that there are a few SNPs with large effects for some traits, these results suggest that polygenicity is ubiquitous for most human complex traits and that a substantial proportion of the “missing heritability” is captured by common SNPs.

Comparative Transcriptome Analysis of Adipose Tissues Reveals that ECM-Receptor Interaction Is Involved in the Depot-Specific Adipogenesis in Cattle.

Adipocytes mainly function as energy storage and endocrine cells. Adipose tissues showed the biological and genetic difference based on their depots. The difference of adipocytes between depots might be influenced by the inherent genetic programing for adipogenesis. We used RNA-seq technique to investigate the transcriptomes in 3 adipose tissues of omental (O), subcutaneous (S) and intramuscular (I) fats in cattle. Sequence reads were obtained from Illumina HiSeq2000 and mapped to the bovine genome using Tophat2. Differentially expressed genes (DEG) between adipose tissues were detected by EdgeR. We identified 5797, 2156, and 5455 DEGs in the comparison between OI, OS, and IS respectively and also found 5657 DEGs in the comparison between the intramuscular and the combined omental and subcutaneous fats (C) (FDR<0.01). Depot specifically up- and down- regulated DEGs were 853 in S, 48 in I, and 979 in O. The numbers of DEGs and functional annotation studies suggested that I had the different genetic profile compared to other two adipose tissues. In I, DEGs involved in the developmental process (eg. EGR2, FAS, and KLF7) were up-regulated and those in the immune system process were down-regulated. Many DEGs from the adipose tissues were enriched in the various GO terms of developmental process and KEGG pathway analysis showed that the ECM-receptor interaction was one of commonly enriched pathways in all of the 3 adipose tissues and also functioned as a sub-pathway of other enriched pathways. However, genes involved in the ECM-receptor interaction were differentially regulated depending on the depots. Collagens, main ECM constituents, were significantly up-regulated in S and integrins, transmembrane receptors, were up-regulated in I. Different laminins were up-regulated in the different depots. This comparative transcriptome analysis of three adipose tissues suggested that the interactions between ECM components and transmembrane receptors of fat cells depend on the depot specific adipogenesis.

African Indigenous Cattle: Unique Genetic Resources in a Rapidly Changing World

At least 150 indigenous African cattle breeds have been named, but the majority of African cattle populations remain largely uncharacterized. As cattle breeds and populations in Africa adapted to various local environmental conditions, they acquired unique features. We know now that the history of African cattle was particularly complex and while several of its episodes remain debated, there is no doubt that African cattle population evolved dramatically over time. Today, we find a mosaic of genetically diverse population from the purest Bos taurus to the nearly pure Bos indicus. African cattle are now found all across the continent, with the exception of the Sahara and the river Congo basin. They are found on the rift valley highlands as well as below sea level in the Afar depression. These unique livestock genetic resources are in danger to disappear rapidly following uncontrolled crossbreeding and breed replacements with exotic breeds. Breeding improvement programs of African indigenous livestock remain too few while paradoxically the demand of livestock products is continually increasing. Many African indigenous breeds are endangered now, and their unique adaptive traits may be lost forever. This paper reviews the unique known characteristics of indigenous African cattle populations while describing the opportunities, the necessity and urgency to understand and utilize these resources to respond to the needs of the people of the continent and to the benefit of African farmers.

Neuronal Genes for Subcutaneous Fat Thickness in Human and Pig Are Identified by Local Genomic Sequencing and Combined SNP Association Study

Obesity represents a major global public health problem that increases the risk for cardiovascular or metabolic disease. The pigs represent an exceptional biomedical model related to energy metabolism and obesity in humans. To pinpoint causal genetic factors for a common form of obesity, we conducted local genomic de novo sequencing, 18.2 Mb, of a porcine QTL region affecting fatness traits, and carried out SNP association studies for backfat thickness and intramuscular fat content in pigs. In order to relate the association studies in pigs to human obesity, we performed a targeted genome wide association study for subcutaneous fat thickness in a cohort population of 8,842 Korean individuals. These combined association studies in human and pig revealed a significant SNP located in a gene family with sequence similarity 73, member A (FAM73A) associated with subscapular skin-fold thickness in humans (rs4121165, GC-corrected p-value  = 0.0000175) and with backfat thickness in pigs (ASGA0029495, p-value  = 0.000031). Our combined association studies also suggest that eight neuronal genes are responsible for subcutaneous fat thickness: NEGR1, SLC44A5, PDE4B, LPHN2, ELTD1, ST6GALNAC3, ST6GALNAC5, and TTLL7. These results provide strong support for a major involvement of the CNS in the genetic predisposition to a common form of obesity.

The genome landscape of indigenous African cattle

BackgroundThe history of African indigenous cattle and their adaptation to environmental and human selection pressure is at the root of their remarkable diversity. Characterization of this diversity is an essential step towards understanding the genomic basis of productivity and adaptation to survival under African farming systems.ResultsWe analyze patterns of African cattle genetic variation by sequencing 48 genomes from five indigenous populations and comparing them to the genomes of 53 commercial taurine breeds. We find the highest genetic diversity among African zebu and sanga cattle. Our search for genomic regions under selection reveals signatures of selection for environmental adaptive traits. In particular, we identify signatures of selection including genes and/or pathways controlling anemia and feeding behavior in the trypanotolerant N’Dama, coat color and horn development in Ankole, and heat tolerance and tick resistance across African cattle especially in zebu breeds.ConclusionsOur findings unravel at the genome-wide level, the unique adaptive diversity of African cattle while emphasizing the opportunities for sustainable improvement of livestock productivity on the continent.

Darkness and gulliver2/phyB mutation decrease the abundance of phosphorylated BZR1 to activate brassinosteroid signaling in Arabidopsis

Light is essential for plant survival; as such, plants flexibly adjust their growth and development to best harvest light energy. Brassinosteroids (BRs), plant growth-promoting steroid hormones, are essential for this plasticity of development. However, the precise mechanisms underlying BR-mediated growth under different light conditions remain largely unknown. Here, we show that darkness increases the activity of the BR-specific transcription factor, BZR1, by decreasing the phosphorylated (inactive) form of BZR1 in a proteasome-dependent manner. We observed that COP1, a dark-activated ubiquitin ligase, captures and degrades the inactive form of BZR1. In support of this, BZR1 is abundant in the cop1-4 mutant. The removal of phosphorylated BZR1 in darkness increases the ratio of dephosphorylated to phosphorylated forms of BZR1, thus increasing the chance of active homodimers forming between dephosphorylated BZR1 proteins. Furthermore, a transcriptome analysis revealed the identity of genes that are likely to contribute to the differential growth of hypocotyls in light conditions. Transgenic misexpression of three genes under the 35S promoter in light conditions resulted in elongated petioles and hypocotyls. Our results suggest that light conditions directly control BR signaling by modulating BZR1 stability, and consequently by establishing light-dependent patterns of hypocotyl growth in Arabidopsis.

Elastic-net regularization approaches for genome-wide association studies of rheumatoid arthritis

The current trend in genome-wide association studies is to identify regions where the true disease-causing genes may lie by evaluating thousands of single-nucleotide polymorphisms (SNPs) across the whole genome. However, many challenges exist in detecting disease-causing genes among the thousands of SNPs. Examples include multicollinearity and multiple testing issues, especially when a large number of correlated SNPs are simultaneously tested. Multicollinearity can often occur when predictor variables in a multiple regression model are highly correlated, and can cause imprecise estimation of association. In this study, we propose a simple stepwise procedure that identifies disease-causing SNPs simultaneously by employing elastic-net regularization, a variable selection method that allows one to address multicollinearity. At Step 1, the single-marker association analysis was conducted to screen SNPs. At Step 2, the multiple-marker association was scanned based on the elastic-net regularization. The proposed approach was applied to the rheumatoid arthritis (RA) case-control data set of Genetic Analysis Workshop 16. While the selected SNPs at the screening step are located mostly on chromosome 6, the elastic-net approach identified putative RA-related SNPs on other chromosomes in an increased proportion. For some of those putative RA-related SNPs, we identified the interactions with sex, a well known factor affecting RA susceptibility.

A genome-wide scan for signatures of directional selection in domesticated pigs

BackgroundAnimal domestication involved drastic phenotypic changes driven by strong artificial selection and also resulted in new populations of breeds, established by humans. This study aims to identify genes that show evidence of recent artificial selection during pig domestication.ResultsWhole-genome resequencing of 30 individual pigs from domesticated breeds, Landrace and Yorkshire, and 10 Asian wild boars at ~16-fold coverage was performed resulting in over 4.3 million SNPs for 19,990 genes. We constructed a comprehensive genome map of directional selection by detecting selective sweeps using an FST-based approach that detects directional selection in lineages leading to the domesticated breeds and using a haplotype-based test that detects ongoing selective sweeps within the breeds. We show that candidate genes under selection are significantly enriched for loci implicated in quantitative traits important to pig reproduction and production. The candidate gene with the strongest signals of directional selection belongs to group III of the metabolomics glutamate receptors, known to affect brain functions associated with eating behavior, suggesting that loci under strong selection include loci involved in behaviorial traits in domesticated pigs including tameness.ConclusionsWe show that a significant proportion of selection signatures coincide with loci that were previously inferred to affect phenotypic variation in pigs. We further identify functional enrichment related to behavior, such as signal transduction and neuronal activities, for those targets of selection during domestication in pigs.