Linkage disequilibrium network analysis (LDna) gives a global view of chromosomal inversions,local adaptation and geographic structure

Recent advances in sequencing allow population‐genomic data to be generated for virtually any species. However, approaches to analyse such data lag behind the ability to generate it, particularly in nonmodel species. Linkage disequilibrium (LD, the nonrandom association of alleles from different loci) is a highly sensitive indicator of many evolutionary phenomena including chromosomal inversions, local adaptation and geographical structure. Here, we present linkage disequilibrium network analysis (LDna), which accesses information on LD shared between multiple loci genomewide. In LD networks, vertices represent loci, and connections between vertices represent the LD between them. We analysed such networks in two test cases: a new restriction‐site‐associated DNA sequence (RAD‐seq) data set for Anopheles baimaii, a Southeast Asian malaria vector; and a well‐characterized single nucleotide polymorphism (SNP) data set from 21 three‐spined stickleback individuals. In each case, we readily identified five distinct LD network clusters (single‐outlier clusters, SOCs), each comprising many loci connected by high LD. In A. baimaii, further population‐genetic analyses supported the inference that each SOC corresponds to a large inversion, consistent with previous cytological studies. For sticklebacks, we inferred that each SOC was associated with a distinct evolutionary phenomenon: two chromosomal inversions, local adaptation, population‐demographic history and geographic structure. LDna is thus a useful exploratory tool, able to give a global overview of LD associated with diverse evolutionary phenomena and identify loci potentially involved. LDna does not require a linkage map or reference genome, so it is applicable to any population‐genomic data set, making it especially valuable for nonmodel species.     

Identification of microRNAs in Macaca fascicularis (Cynomolgus Monkey) by Homology Search and Experimental Validation by Small RNA-Seq and RT-qPCR Using Kidney Cortex Tissues

MicroRNAs (miRNAs) present in tissues and biofluids are emerging as sensitive and specific safety biomarkers. MiRNAs have not been thoroughly described in M. fascicularis, an animal model used in pharmaceutical industry especially in drug safety evaluation. Here we investigated the miRNAs in M. fascicularis. For Macaca mulatta, a closely related species of M. fascicularis, 619 stem-loop precursor miRNAs (pre-miRNAs) and 914 mature miRNAs are available in miRBase version 21. Using M. mulatta miRNAs as a reference list and homology search tools, we identified 604 pre-miRNAs and 913 mature miRNAs in the genome of M. fascicularis. In order to validate the miRNAs identified by homology search we attempted to sequence miRNAs expressed in kidney cortex from M. fascicularis. MiRNAs expressed in kidney cortex may indeed be released in urine upon kidney cortex damage and be potentially used to monitor drug induced kidney injury. Hence small RNA sequencing libraries were prepared using kidney cortex tissues obtained from three naive M. fascicularis and sequenced. Analysis of sequencing data indicated that 432 out of 913 mature miRNAs were expressed in kidney cortex tissues. Assigning these 432 miRNAs to pre-miRNAs revealed that 273 were expressed from both the -5p and -3p arms of 150 pre-miRNAs and 159 miRNAs expressed from either the -5p or -3p arm of 176 pre-miRNAs. Mapping sequencing reads to pre-miRNAs also facilitated the detection of twenty-two new miRNAs. To substantiate miRNAs identified by small RNA sequencing, 313 miRNAs were examined by RT-qPCR. Expression of 262 miRNAs in kidney cortex tissues ware confirmed by TaqMan microRNA RT-qPCR assays. Analysis of kidney cortex miRNA targeted genes suggested that they play important role in kidney development and function. Data presented in this study may serve as a valuable resource to assess the renal safety biomarker potential of miRNAs in Cynomolgus monkeys.     

Phosphate Homeostasis in Conditions of Phosphate Proficiency and Limitation in the Wild Type and the phoP Mutant of Streptomyces lividans

Phosphate, as a constituent of the high energy molecules, ATP/GTP and polyphosphate, plays a crucial role in most of the metabolic processes of living organisms. Therefore, the adaptation to low Pi availability is a major challenge for bacteria. In Streptomyces, this adaptation is tightly controlled by the two component PhoR/PhoP system. In this study, the free intracellular Pi, ATP, ADP and polyP content of the wild type and the phoP mutant strain of S. lividans TK24 were analyzed at discrete time points throughout growth in Pi replete and limited media. PolyP length and content was shown to be directly related to the Pi content of the growth medium. In Pi repletion, ATP and high molecular weight (HMW) polyP contents were higher in the phoP mutant than in the WT strain. This supports the recently proposed repressive effect of PhoP on oxidative phosphorylation. High oxidative phosphorylation activity might also have a direct or indirect positive impact on HMW polyP synthesis. In Pi sufficiency as in Pi limitation, the degradation of these polymers was shown to be clearly delayed in the phoP mutant, indicating PhoP dependent expression of the enzymes involved in this degradation. The efficient storage of Pi as polyphosphate and/or its inefficient degradation in Pi in the phoP mutant resulted in low levels of free Pi and ATP that are likely to be, at least in part, responsible for the very poor growth of this mutant in Pi limitation. Furthermore, short polyP was shown to be present outside the cell, tightly bound to the mycelium via electrostatic interactions involving divalent cations. Less short polyP was found to be associated with the mycelium of the phoP mutant than with that of the WT strain, indicating that generation and externalization of these short polyP molecules was directly or indirectly dependent on PhoP.     

Having a Lot of a Good Thing: Multiple Important Group Memberships as a Source of Self-Esteem

Membership in important social groups can promote a positive identity. We propose and test an identity resource model in which personal self-esteem is boosted by membership in additional important social groups. Belonging to multiple important group memberships predicts personal self-esteem in children (Study 1a), older adults (Study 1b), and former residents of a homeless shelter (Study 1c). Study 2 shows that the effects of multiple important group memberships on personal self-esteem are not reducible to number of interpersonal ties. Studies 3a and 3b provide longitudinal evidence that multiple important group memberships predict personal self-esteem over time. Studies 4 and 5 show that collective self-esteem mediates this effect, suggesting that membership in multiple important groups boosts personal self-esteem because people take pride in, and derive meaning from, important group memberships. Discussion focuses on when and why important group memberships act as a social resource that fuels personal self-esteem.     

Prediction of Recurrence and Survival for Triple-Negative Breast Cancer (TNBC) by a Protein Signature in Tissue Samples

To date, there is no available targeted therapy for patients who are diagnosed with triple-negative breast cancers (TNBC). The aim of this study was to identify a new specific target for specific treatments. Frozen primary tumors were collected from 83 adjuvant therapy-naive TNBC patients. These samples were used for global proteome profiling by iTRAQ-OFFGEL-LC-MS/MS approach in two series: a training cohort (n = 42) and a test set (n = 41). Patients who remains free of local or distant metastasis for a minimum of 5 years after surgery were classified in the no-relapse group; the others were in the relapse group. OPLS and Kaplan–Meier analyses were performed to select candidate markers, which were validated by immunohistochemistry. Three proteins were identified in the training set and validated in the test set by Kaplan–Meier method and immunohistochemistry (IHC): TrpRS as a good prognostic markers and DP and TSP1 as bad prognostic markers. We propose the establishment of an IHC test to calculate the score of TrpRS, DP, and TSP1 in TNBC tumors to evaluate the degree of aggressiveness of the tumors. Finally, we propose that DP and TSP1 could provide therapeutic targets for specific treatments.Triple-negative breast cancers (TNBC)¹ are defined by a lack of expression of estrogen (ER), progesterone (PR), and HER2/neu receptors and account for about 15% of all breast cancers. This subtype is associated with poor prognosis (1) in terms of distant free survival (DFS) and overall survival (OS), and to date, there is no clinically available targeted therapy for patients diagnosed with TNBC. Because of the absence of specific treatment guidelines for this group of patients, TNBC are managed with standard adjuvant chemotherapy (2), which, however, seems to be less effective in those cancers. In order to improve survival, it is important to determine new specific-targeted treatment.A proteomic analysis has several inherent advantages over a genomic approach in that measured mRNA levels do not necessarily correlate to corresponding protein levels. In addition, protein detection is probably also more reflective of the tumor microenvironment. Several proteomic studies have been conducted on TNBC (3–5), but no proteomic study was conducted on large cohorts including the clinical outcome of the patients, except a recent comparative proteome analysis that identified a 11-protein signature for aggressive TNBC in a large cohort of 93 microdissected tumors (6). Although microdissection was necessary to elucidate the contribution of TNBC cells, it did not reflect the tumor with its microenvironment that is increasingly described as fundamental to explain the tumor outcome. Thus, it is now recognized that carcinomas derive from phenomena that occur in tissues, not in individual cancer cells. From this perspective, the microenvironment becomes an integral, essential part of the tumor (7, 8). In this context, taking into account the tumor microenvironment, we investigated a cohort of 83 TNBC samples without microdissection by a quantitative proteomic approach using iTRAQ labeling. Based on clinical data, we established a protein signature of the most aggressive tumors. From these differentially expressed proteins, some of them appeared to be potential therapeutic targets.     

Prospective Large-Scale Field Study Generates Predictive Model Identifying Major Contributors to Colony Losses

Over the last decade, unusually high losses of colonies have been reported by beekeepers across the USA. Multiple factors such as Varroa destructor, bee viruses, Nosema ceranae, weather, beekeeping practices, nutrition, and pesticides have been shown to contribute to colony losses. Here we describe a large-scale controlled trial, in which different bee pathogens, bee population, and weather conditions across winter were monitored at three locations across the USA. In order to minimize influence of various known contributing factors and their interaction, the hives in the study were not treated with antibiotics or miticides. Additionally, the hives were kept at one location and were not exposed to potential stress factors associated with migration. Our results show that a linear association between load of viruses (DWV or IAPV) in Varroa and bees is present at high Varroa infestation levels (>3 mites per 100 bees). The collection of comprehensive data allowed us to draw a predictive model of colony losses and to show that Varroa destructor, along with bee viruses, mainly DWV replication, contributes to approximately 70% of colony losses. This correlation further supports the claim that insufficient control of the virus-vectoring Varroa mite would result in increased hive loss. The predictive model also indicates that a single factor may not be sufficient to trigger colony losses, whereas a combination of stressors appears to impact hive health.