Genome-wide association studies of 14 agronomic traits in rice landraces

Uncovering the genetic basis of agronomic traits in crop landraces that have adapted to various agro-climatic conditions is important to world food security. Here we have identified ～ 3.6 million SNPs by sequencing 517 rice landraces and constructed a high-density haplotype map of the rice genome using a novel data-imputation method. We performed genome-wide association studies (GWAS) for 14 agronomic traits in the population of Oryza sativa indica subspecies. The loci identified through GWAS explained ～ 36% of the phenotypic variance, on average. The peak signals at six loci were tied closely to previously identified genes. This study provides a fundamental resource for rice genetics research and breeding, and demonstrates that an approach integrating second-generation genome sequencing and GWAS can be used as a powerful complementary strategy to classical biparental cross-mapping for dissecting complex traits in rice.     

Exome sequencing of liver fluke-associated cholangiocarcinoma

Opisthorchis viverrini-related cholangiocarcinoma (CCA), a fatal bile duct cancer, is a major public health concern in areas endemic for this parasite. We report here whole-exome sequencing of eight O. viverrini-related tumors and matched normal tissue. We identified and validated 206 somatic mutations in 187 genes using Sanger sequencing and selected 15 genes for mutation prevalence screening in an additional 46 individuals with CCA (cases). In addition to the known cancer-related genes TP53 (mutated in 44.4% of cases), KRAS (16.7%) and SMAD4 (16.7%), we identified somatic mutations in 10 newly implicated genes in 14.8-3.7% of cases. These included inactivating mutations in MLL3 (in 14.8% of cases), ROBO2 (9.3%), RNF43 (9.3%) and PEG3 (5.6%), and activating mutations in the GNAS oncogene (9.3%). These genes have functions that can be broadly grouped into three biological classes: (i) deactivation of histone modifiers, (ii) activation of G protein signaling and (iii) loss of genome stability. This study provides insight into the mutational landscape contributing to O. viverrini-related CCA.     

Common variants at 12q14 and 12q24 are associated with hippocampal volume

Aging is associated with reductions in hippocampal volume that are accelerated by Alzheimer's disease and vascular risk factors. Our genome-wide association study (GWAS) of dementia-free persons (n = 9,232) identified 46 SNPs at four loci with P values of <4.0 × 10(-7). In two additional samples (n = 2,318), associations were replicated at 12q14 within MSRB3-WIF1 (discovery and replication; rs17178006; P = 5.3 × 10(-11)) and at 12q24 near HRK-FBXW8 (rs7294919; P = 2.9 × 10(-11)). Remaining associations included one SNP at 2q24 within DPP4 (rs6741949; P = 2.9 × 10(-7)) and nine SNPs at 9p33 within ASTN2 (rs7852872; P = 1.0 × 10(-7)); along with the chromosome 12 associations, these loci were also associated with hippocampal volume (P < 0.05) in a third younger, more heterogeneous sample (n = 7,794). The SNP in ASTN2 also showed suggestive association with decline in cognition in a largely independent sample (n = 1,563). These associations implicate genes related to apoptosis (HRK), development (WIF1), oxidative stress (MSR3B), ubiquitination (FBXW8) and neuronal migration (ASTN2), as well as enzymes targeted by new diabetes medications (DPP4), indicating new genetic influences on hippocampal size and possibly the risk of cognitive decline and dementia.     

Genome-wide association study of flowering time and grain yield traits in a worldwide collection of rice germplasm

A high-density haplotype map recently enabled a genome-wide association study (GWAS) in a population of indica subspecies of Chinese rice landraces. Here we extend this methodology to a larger and more diverse sample of 950 worldwide rice varieties, including the Oryza sativa indica and Oryza sativa japonica subspecies, to perform an additional GWAS. We identified a total of 32 new loci associated with flowering time and with ten grain-related traits, indicating that the larger sample increased the power to detect trait-associated variants using GWAS. To characterize various alleles and complex genetic variation, we developed an analytical framework for haplotype-based de novo assembly of the low-coverage sequencing data in rice. We identified candidate genes for 18 associated loci through detailed annotation. This study shows that the integrated approach of sequence-based GWAS and functional genome annotation has the potential to match complex traits to their causal polymorphisms in rice.     

A genome-wide association study in Han Chinese identifies new susceptibility loci for ankylosing spondylitis

To identify susceptibility loci for ankylosing spondylitis, we performed a two-stage genome-wide association study in Han Chinese. In the discovery stage, we analyzed 1,356,350 autosomal SNPs in 1,837 individuals with ankylosing spondylitis and 4,231 controls; in the validation stage, we analyzed 30 suggestive SNPs in an additional 2,100 affected individuals and 3,496 controls. We identified two new susceptibility loci between EDIL3 and HAPLN1 at 5q14.3 (rs4552569; P = 8.77 × 10(-10)) and within ANO6 at 12q12 (rs17095830; P = 1.63 × 10(-8)). We also confirmed previously reported associations in Europeans within the major histocompatibility complex (MHC) region (top SNP, rs13202464; P < 5 × 10(-324)) and at 2p15 (rs10865331; P = 1.98 × 10(-8)). We show that rs13202464 within the MHC region mainly represents the risk effect of HLA-B*27 variants (including HLA-B*2704, HLA-B*2705 and HLA-B*2715) in Chinese. The two newly discovered loci implicate genes related to bone formation and cartilage development, suggesting their potential involvement in the etiology of ankylosing spondylitis.     

Frequent mutations of chromatin remodeling genes in transitional cell carcinoma of the bladder

Transitional cell carcinoma (TCC) is the most common type of bladder cancer. Here we sequenced the exomes of nine individuals with TCC and screened all the somatically mutated genes in a prevalence set of 88 additional individuals with TCC with different tumor stages and grades. In our study, we discovered a variety of genes previously unknown to be mutated in TCC. Notably, we identified genetic aberrations of the chromatin remodeling genes (UTX, MLL-MLL3, CREBBP-EP300, NCOR1, ARID1A and CHD6) in 59% of our 97 subjects with TCC. Of these genes, we showed UTX to be altered substantially more frequently in tumors of low stages and grades, highlighting its potential role in the classification and diagnosis of bladder cancer. Our results provide an overview of the genetic basis of TCC and suggest that aberration of chromatin regulation might be a hallmark of bladder cancer.     

Drosophila Piwi functions in Hsp90-mediated suppression of phenotypic variation

Canalization, also known as developmental robustness, describes an organism's ability to produce the same phenotype despite genotypic variations and environmental influences. In Drosophila, Hsp90, the trithorax-group proteins and transposon silencing have been previously implicated in canalization. Despite this, the molecular mechanism underlying canalization remains elusive. Here using a Drosophila eye-outgrowth assay sensitized by the dominant Kr(irregular facets-1)(Kr(If-1)) allele, we show that the Piwi-interacting RNA (piRNA) pathway, but not the short interfering RNA or micro RNA pathway, is involved in canalization. Furthermore, we isolated a protein complex composed of Hsp90, Piwi and Hop, the Hsp70/Hsp90 organizing protein homolog, and we demonstrated the function of this complex in canalization. Our data indicate that Hsp90 and Hop regulate the piRNA pathway through Piwi to mediate canalization. Moreover, they point to epigenetic silencing of the expression of existing genetic variants and the suppression of transposon-induced new genetic variation as two major mechanisms underlying piRNA pathway-mediated canalization.     

A Hierarchical Ensemble Learning Framework for Energy-Efficient Automatic Train Driving

Railway transportation plays an important role in modern society. As China's massive railway transportation network continues to grow in total mileage and operation density, the energy consumption of trains becomes a serious concern. For any given route, the geographic characteristics are known a priori, but the parameters(e.g., loading and marshaling) of trains vary from one trip to another. An extensive analysis of the train operation data suggests that the control gear operation of trains is the most important factor that affects the energy consumption. Such an observation determines that the problem of energy-efficient train driving has to be addressed by considering both the geographic information and the trip parameters. However, the problem is difficult to solve due to its high dimension, nonlinearity, complex constraints, and time-varying characteristics. Faced with these difficulties, we propose an energy-efficient train control framework based on a hierarchical ensemble learning approach. Through hierarchical refinement, we learn prediction models of speed and gear. The learned models can be used to derive optimized driving operations under real-time requirements. This study uses random forest and bagging – REPTree as classification algorithm and regression algorithm, respectively. We conduct an extensive study on the potential of bagging, decision trees, random forest, and feature selection to design an effective hierarchical ensemble learning framework. The proposed framework was testified through simulation. The average energy consumption of the proposed method is over 7% lower than that of human drivers.