GITAR: An Open Source Tool for Analysis and Visualization of Hi-C Data

Interactions between chromatin segments play a large role in functional genomic assays and developments in genomic interaction detection methods have shown interacting topological domains within the genome. Among these methods, Hi-C plays a key role. Here, we present the Genome Interaction Tools and Resources (GITAR), a software to perform a comprehensive Hi-C data analysis, including data preprocessing, normalization, and visualization, as well as analysis of topologically-associated domains (TADs). GITAR is composed of two main modules: (1) HiCtool, a Python library to process and visualize Hi-C data, including TAD analysis; and (2) processed data library, a large collection of human and mouse datasets processed using HiCtool. HiCtool leads the user step-by-step through a pipeline, which goes from the raw Hi-C data to the computation, visualization, and optimized storage of intra-chromosomal contact matrices and TAD coordinates. A large collection of standardized processed data allows the users to compare different datasets in a consistent way, while saving time to obtain data for visualization or additional analyses. More importantly, GITAR enables users without any programming or bioinformatic expertise to work with Hi-C data. GITAR is publicly available at http://genomegitar.org as an open-source software.     

QTL mapping of flag leaf-related traits in wheat (<Emphasis Type="Italic">Triticum aestivum</Emphasis> L.)

Key message

QTL controlling flag leaf length, flag leaf width, flag leaf area and flag leaf angle were mapped in wheat.

Abstract

This study aimed to advance our understanding of the genetic mechanisms underlying morphological traits of the flag leaves of wheat (Triticum aestivum L.). A recombinant inbred line (RIL) population derived from ND3331 and the Tibetan semi-wild wheat Zang1817 was used to identify quantitative trait loci (QTLs) controlling flag leaf length (FLL), flag leaf width (FLW), flag leaf area (FLA), and flag leaf angle (FLANG). Using an available simple sequence repeat genetic linkage map, 23 putative QTLs for FLL, FLW, FLA, and FLANG were detected on chromosomes 1B, 2B, 3A, 3D, 4B, 5A, 6B, 7B, and 7D. Individual QTL explained 4.3–68.52% of the phenotypic variance in different environments. Four QTLs for FLL, two for FLW, four for FLA, and five for FLANG were detected in at least two environments. Positive alleles of 17 QTLs for flag leaf-related traits originated from ND3331 and 6 originated from Zang1817. QTLs with pleiotropic effects or multiple linked QTL were also identified on chromosomes 1B, 4B, and 5A; these are potential target regions for fine-mapping and marker-assisted selection in wheat breeding programs.

     

Genetic dissection of wheat panicle traits using linkage analysis and a genome-wide association study

Key message

Coincident regions on chromosome 4B for GW, on 5A for SD and TSS, and on 3A for SL and GNS were detected through an integration of a linkage analysis and a genome-wide association study (GWAS). In addition, six stable QTL clusters on chromosomes 2D, 3A, 4B, 5A and 6A were identified with high PVE% on a composite map.

Abstract

The panicle traits of wheat, such as grain number per spike and 1000-grain weight, are closely correlated with grain yield. Superior and effective alleles at loci related to panicles developments play a crucial role in the progress of molecular improvement in wheat yield breeding. Here, we revealed several notable allelic variations of seven panicle-related traits through an integration of genome-wide association mapping and a linkage analysis. The linkage analysis was performed using a recombinant inbred line (RIL) population (173 lines of F_8:9) with a high-density genetic map constructed with 90K SNP arrays, Diversity Arrays Technology (DArT) and simple sequence repeat (SSR) markers in five environments. Thirty-five additive quantitative trait loci (QTL) were discovered, including eleven stable QTLs on chromosomes 1A, 2D, 4B, 5B, 6B, and 6D. The marker interval between EX_C101685 and RAC875_C27536 on chromosome 4B exhibited pleiotropic effects for GW, SL, GNS, FSN, SSN, and TSS, with the phenotypic variation explained (PVE) ranging from 5.40 to 37.70%. In addition, an association analysis was conducted using a diverse panel of 205 elite wheat lines with a composite map (24,355 SNPs) based on the Illumina Infinium assay in four environments. A total of 73 significant marker-trait associations (MTAs) were detected for panicle traits, which were distributed across all wheat chromosomes except for 4D, 5D, and 6D. Consensus regions between RAC875_C27536_611 and Tdurum_contig4974_355 on chromosome 4B for GW in multiple environments, between QTSS5A.7-43 and BS00021805_51 on 5A for SD and TSS, and between QSD3A.2-164 and RAC875_c17479_359 on 3A for SL and GNS in multiple environments were detected through linkage analysis and a genome-wide association study (GWAS). In addition, six stable QTL clusters on chromosomes 2D, 3A, 4B, 5A, and 6A were identified with high PVE% on a composite map. This study provides potentially valuable information on the dissection of yield-component traits and valuable genetic alleles for molecular-design breeding or functional gene exploration.

     

Spheroids from adipose‐derived stem cells exhibit an miRNA profile of highly undifferentiated cells

Two‐dimensional (2D) cell cultures have been extensively used to investigate stem cell biology, but new insights show that the 2D model may not properly represent the potential of the tissue of origin. Conversely, three‐dimensional cultures exhibit protein expression patterns and intercellular junctions that are more representative of their in vivo condition. Multiclonal cells that grow in suspension are defined as “spheroids,” and we have previously demonstrated that spheroids from adipose‐derived stem cells (S‐ASCs) displayed enhanced regenerative capability. With the current study, we further characterized S‐ASCs to further understand the molecular mechanisms underlying their stemness properties. Recent studies have shown that microRNAs (miRNAs) are involved in many cellular mechanisms, including stemness maintenance and proliferation, and adipose stem cell differentiation. Most studies have been conducted to identify a specific miRNA profile on adherent adipose stem cells, although little is still known about S‐ASCs. In this study, we investigate for the first time the miRNA expression pattern in S‐ASCs compared to that of ASCs, demonstrating that cell lines cultured in suspension show a typical miRNA expression profile that is closer to the one reported in induced pluripotent stem cells. Moreover, we have analyzed miRNAs that are specifically involved in two distinct moments of each differentiation, namely early and late stages of osteogenic, adipogenic, and chondrogenic lineages during long‐term in vitro culture. The data reported in the current study suggest that S‐ASCs have superior stemness features than the ASCs and they represent the true upstream stem cell fraction present in adipose tissue, relegating their adherent counterparts.     

Long non‐coding RNA TCONS_00041960 enhances osteogenesis and inhibits adipogenesis of rat bone marrow mesenchymal stem cell by targeting miR‐204‐5p and miR‐125a‐3p

A growing number of long non‐coding RNAs (lncRNAs) have been found to be involved in diverse biological processes such as cell cycle regulation, embryonic development, and cell differentiation. However, limited knowledge is available concerning the underlying mechanisms of lncRNA functions. In this study, we found down‐regulation of TCONS_00041960 during adipogenic and osteogenic differentiation of glucocorticoid‐treated bone marrow mesenchymal stem cells (BMSCs). Furthermore, up‐regulation of TCONS_00041960 promoted expression of osteogenic genes Runx2, osterix, and osteocalcin, and anti‐adipogenic gene glucocorticoid‐induced leucine zipper (GILZ). Conversely, expression of adipocyte‐specific markers was decreased in the presence of over‐expressed TCONS_00041960. Mechanistically, we determined that TCONS_00041960 as a competing endogenous RNA interacted with miR‐204‐5p and miR‐125a‐3p to regulate Runx2 and GILZ, respectively. Overall, we identified a new TCONS_00041960‐miR‐204‐5p/miR‐125a‐3p‐Runx2/GILZ axis involved in regulation of adipogenic and osteogenic differentiation of glucocorticoid‐treated BMSCs.     

The Rice <Emphasis Type="Italic">OsDUF810</Emphasis> Family: OsDUF810.7 May be Involved in the Tolerance to Salt and Drought

With the advance of sequencing technology, the number of sequenced plant genomes has been rapidly increasing. However, understanding of the gene function in these sequenced genomes lags far behind; as a result, many coding plant sequences in public databases are annotated as proteins with domains of unknown function (DUF). Function of a protein family DUF810 in rice is not known. In this study, we analysed seven members of OsDU810 (OsDUF810.1–OsDUF810.7) family with three distinct motifs in rice Nipponbare. By phylogenetic analysis, OsDUF810 proteins fall into three major groups (I, II, III). Expression patterns of the seven corresponding OsDUF810 protein-encoding genes in 15 different rice tissues vary. Under drought, salt, cold and heat stress conditions and ABA treatment, the expression of OsDUF810.7 significantly increases. Overexpression of this protein in E. coli lead to a significant enhancement of catalase (CAT) and peroxidase (POD) activities, and improved bacterial resistance to salt and drought.