A functional variant in SLC1A3 influences ADHD risk by disrupting a hsa‐miR‐3171 binding site: A two‐stage association study

Attention‐deficit hyperactivity disorder (ADHD) is one of the most common neuropsychiatric disorders in children and adolescents with high heritability. Evidence is accumulating that SLC1A3 may play a role in ADHD etiology. Therefore, a two‐stage case‐control study was conducted on 752 cases and 774 controls to explore the role of SLC1A3 in ADHD. Bioinformatic annotations and functional experiments were applied to reveal the potential biological mechanisms. Finally, SLC1A3 rs1049522 showed significant association with ADHD risk in two stages with CA genotype vs AA genotype, odds ratio (OR) = 0.694 (95% confidence interval, CI = 0.570‐0.844) and dominant model, OR = 0.749 (95% CI = 0.621‐0.904) in the combined stage. Besides, rs1049522 was found to be related to ADHD hyperactive/impulsive symptom, and rs1049522‐C showed increased SLC1A3 mRNA expression in the cerebellar cortex. Dual‐luciferase reporter assay further indicated that rs1049522‐C allele enhanced SLC1A3 expression by disrupting the hsa‐miR‐3171 binding site. In conclusion, SLC1A3 variant rs1049522 was implicated in ADHD susceptibility in a Chinese Han population probably by enhancing the SLC1A3 expression in a miRNA‐mediated manner.     

A QTL on chromosome 3q23 influences processing speed in humans

Processing speed is a psychological construct that refers to the speed with which an individual can perform any cognitive operation. Processing speed correlates strongly with general cognitive ability, declines sharply with age and is impaired across a number of neurological and psychiatric disorders. Thus, identifying genes that influence processing speed will likely improve understanding of the genetics of intelligence, biological aging and the etiologies of numerous disorders. Previous genetics studies of processing speed have relied on simple phenotypes (eg, mean reaction time) derived from single tasks. This strategy assumes, erroneously, that processing speed is a unitary construct. In the present study, we aimed to characterize the genetic architecture of processing speed by using a multidimensional model applied to a battery of cognitive tasks. Linkage and QTL‐specific association analyses were performed on the factors from this model. The randomly ascertained sample comprised 1291 Mexican‐American individuals from extended pedigrees. We found that performance on all three distinct processing‐speed factors (Psychomotor Speed; Sequencing and Shifting and Verbal Fluency) were moderately and significantly heritable. We identified a genome‐wide significant quantitative trait locus (QTL) on chromosome 3q23 for Psychomotor Speed (LOD = 4.83). Within this locus, we identified a plausible and interesting candidate gene for Psychomotor Speed (Z = 2.90, P = 1.86 × 10^?03).     

Autographa Californica Multiple Nucleopolyhedrovirus P48 (Ac103) Is Required for the Efficient Formation of Virus-Induced Intranuclear Microvesicles

Our previous study has shown that the Autographa californica multiple nucleopolyhedrovirus(AcMNPV) p48(ac103)gene is essential for the nuclear egress of nucleocapsids and the formation of occlusion-derived virions(ODVs). However,the exact role of p48 in the morphogenesis of ODVs remains unknown. In this study, we demonstrated that p48 was required for the efficient formation of intranuclear microvesicles. To further understand its functional role in intranuclear microvesicle formation, we characterized the distribution of the P48 protein, which was found to be associated with the nucleocapsid and envelope fractions of both budded virions and ODVs. In Ac MNPV-infected cells, P48 was predominantly localized to nucleocapsids in the virogenic stroma and the nucleocapsids enveloped in ODVs, with a limited but discernible distribution in the plasma membrane, nuclear envelope, intranuclear microvesicles, and ODV envelope. Furthermore,coimmunoprecipitation assays showed that among the viral proteins required for intranuclear microvesicle formation, P48 associated with Ac93 in the absence of viral infection.     

Comparative population genomics identified genomic regions and candidate genes associated with fruit domestication traits in peach

Crop evolution is a long‐term process involving selection by natural evolutionary forces and anthropogenic influences; however, the genetic mechanisms underlying the domestication and improvement of fruit crops have not been well studied to date. Here, we performed a population structure analysis in peach (Prunus persica) based on the genome‐wide resequencing of 418 accessions and confirmed the presence of an obvious domestication event during evolution. We identified 132 and 106 selective sweeps associated with domestication and improvement, respectively. Analysis of their tissue‐specific expression patterns indicated that the up‐regulation of selection genes during domestication occurred mostly in fruit and seeds as opposed to other organs. However, during the improvement stage, more up‐regulated selection genes were identified in leaves and seeds than in the other organs. Genome‐wide association studies (GWAS) using 4.24 million single nucleotide polymorphisms (SNPs) revealed 171 loci associated with 26 fruit domestication traits. Among these loci, three candidate genes were highly associated with fruit weight and the sorbitol and catechin content in fruit. We demonstrated that as the allele frequency of the SNPs associated with high polyphenol composition decreased during peach evolution, alleles associated with high sugar content increased significantly. This indicates that there is genetic potential for the breeding of more nutritious fruit with enhanced bioactive polyphenols without disturbing a harmonious sugar and acid balance by crossing with wild species. This study also describes the development of the genomic resources necessary for evolutionary research in peach and provides the large‐scale characterization of key agronomic traits in this crop species.     

Rapid identification and interpretation of gene–environment associations using the new R.SamBada landscape genomics pipeline

sam βada is a genome–environment association software, designed to search for signatures of local adaptation. However, pre‐ and postprocessing of data can be labour‐intensive, preventing wider uptake of the method. We have now developed R.SamBada, an r ‐package providing a pipeline for landscape genomic analysis based on sam βada , spanning from the retrieval of environmental conditions at sampling locations to gene annotation using the Ensembl genome browser. As a result, R.SamBada standardizes the landscape genomics pipeline and eases the search for candidate genes of local adaptation, enhancing reproducibility of landscape genomic studies. The efficiency and power of the pipeline is illustrated using two examples: sheep populations from Morocco with no evident population structure and Lidia cattle from Spain displaying population substructuring. In both cases, R.SamBada enabled rapid identification and interpretation of candidate genes, which are further discussed in the light of local adaptation. The package is available in the r CRAN package repository and on GitHub (github.com/SolangeD/R.SamBada).     

Leveraging GWAS data to identify metabolic pathways and networks involved in maize lipid biosynthesis

Maize (Zea mays mays) oil is a rich source of polyunsaturated fatty acids (FAs) and energy, making it a valuable resource for human food, animal feed, and bio‐energy. Although this trait has been studied via conventional genome‐wide association study (GWAS), the single nucleotide polymorphism (SNP)‐trait associations generated by GWAS may miss the underlying associations when traits are based on many genes, each with small effects that can be overshadowed by genetic background and environmental variation. Detecting these SNPs statistically is also limited by the levels set for false discovery rate. A complementary pathways analysis that emphasizes the cumulative aspects of SNP‐trait associations, rather than just the significance of single SNPs, was performed to understand the balance of lipid metabolism, conversion, and catabolism in this study. This pathway analysis indicated that acyl‐lipid pathways, including biosynthesis of wax esters, sphingolipids, phospholipids and flavonoids, along with FA and triacylglycerol (TAG) biosynthesis, were important for increasing oil and FA content. The allelic variation found among the genes involved in many degradation pathways, and many biosynthesis pathways leading from FAs and carbon partitioning pathways, was critical for determining final FA content, changing FA ratios and, ultimately, to final oil content. The pathways and pathway networks identified in this study, and especially the acyl‐lipid associated pathways identified beyond what had been found with GWAS alone, provide a real opportunity to precisely and efficiently manipulate high‐oil maize genetic improvement.     

Genetic and genomic resources of sorghum to connect genotype with phenotype in contrasting environments

With the recent development of genomic resources and high‐throughput phenotyping platforms, the 21st century is primed for major breakthroughs in the discovery, understanding and utilization of plant genetic variation. Significant advances in agriculture remain at the forefront to increase crop production and quality to satisfy the global food demand in a changing climate all while reducing the environmental impacts of the world's food production. Sorghum, a resilient C₄ grain and grass important for food and energy production, is being extensively dissected genetically and phenomically to help connect the relationship between genetic and phenotypic variation. Unlike genetically modified crops such as corn or soybean, sorghum improvement has relied heavily on public research; thus, many of the genetic resources serve a dual purpose for both academic and commercial pursuits. Genetic and genomic resources not only provide the foundation to identify and understand the genes underlying variation, but also serve as novel sources of genetic and phenotypic diversity in plant breeding programs. To better disseminate the collective information of this community, we discuss: (i) the genomic resources of sorghum that are at the disposal of the research community; (ii) the suite of sorghum traits as potential targets for increasing productivity in contrasting environments; and (iii) the prospective approaches and technologies that will help to dissect the genotype–phenotype relationship as well as those that will apply foundational knowledge for sorghum improvement.     

Genetic association with high‐resolution climate data reveals selection footprints in the genomes of barley landraces across the Iberian Peninsula

Landraces are local populations of crop plants adapted to a particular environment. Extant landraces are surviving genetic archives, keeping signatures of the selection processes experienced by them until settling in their current niches. This study intends to establish relationships between genetic diversity of barley (Hordeum vulgare L.) landraces collected in Spain and the climate of their collection sites. A high‐resolution climatic data set (5 × 5 km spatial, 1‐day temporal grid) was computed from over 2,000 temperature and 7,000 precipitation stations across peninsular Spain. This data set, spanning the period 1981–2010, was used to derive agroclimatic variables meaningful for cereal production at the collection sites of 135 barley landraces. Variables summarize temperature, precipitation, evapotranspiration, potential vernalization and frost probability at different times of the year and time scales (season and month). SNP genotyping of the landraces was carried out combining Illumina Infinium assays and genotyping‐by‐sequencing, yielding 9,920 biallelic markers (7,479 with position on the barley reference genome). The association of these SNPs with agroclimatic variables was analysed at two levels of genetic diversity, with and without taking into account population structure. The whole data sets and analysis pipelines are documented and available at https://eead-csic-compbio.github.io/barley-agroclimatic-association . We found differential adaptation of the germplasm groups identified to be dominated by reactions to cold temperature and late‐season frost occurrence, as well as to water availability. Several significant associations pointing at specific adaptations to agroclimatic features related to temperature and water availability were observed, and candidate genes underlying some of the main regions are proposed.     

粤东亚热带森林群落树种组成对苔藓植物分布的影响

为探究森林群落树种组成对苔藓植物分布的影响,利用多元统计方法研究粤东亚热带地区苔藓植物的组成和分布对林分类型的响应。根据森林乔木层的树种组成划分为翻白叶树(Pterospermum heterophyllum)、木荷(Schima superba)+米锥(Castanopsis carlesii)和米锥3种森林类型。结果表明,3种森林类型中苔类(liverworts)和藓类(mosses)植物群落组成特征总体上存在显著差异;双齿裂萼苔(Chiloscyphus latifolius)和细指苔(Kurzia gonyotricha)在3种类型林分中的重要值变化指示了苔类植物群落的差异。3种类型林分中,均以东亚拟鳞叶藓(Pseudotaxiphyllum pohliaecarpum)为优势种。不同林分中藓类植物种类组成主要表现为亚优种分布的不同。这表明森林群落树种组成作为重要的生物因子,对林内苔藓植物的分布和种类组成有重要影响。