The small RNA content of human sperm reveals pseudogene-derived piRNAs complementary to protein-coding genes

At the end of mammalian sperm development, sperm cells expel most of their cytoplasm and dispose of the majority of their RNA. Yet, hundreds of RNA molecules remain in mature sperm. The biological significance of the vast majority of these molecules is unclear. To better understand the processes that generate sperm small RNAs and what roles they may have, we sequenced and characterized the small RNA content of sperm samples from two human fertile individuals. We detected 182 microRNAs, some of which are highly abundant. The most abundant microRNA in sperm is miR-1246 with predicted targets among sperm-specific genes. The most abundant class of small noncoding RNAs in sperm are PIWI-interacting RNAs (piRNAs). Surprisingly, we found that human sperm cells contain piRNAs processed from pseudogenes. Clusters of piRNAs from human testes contain pseudogenes transcribed in the antisense strand and processed into small RNAs. Several human protein-coding genes contain antisense predicted targets of pseudogene-derived piRNAs in the male germline and these piRNAs are still found in mature sperm. Our study provides the most extensive data set and annotation of human sperm small RNAs to date and is a resource for further functional studies on the roles of sperm small RNAs. In addition, we propose that some of the pseudogene-derived human piRNAs may regulate expression of their parent gene in the male germline.     

Does coping style predict optimization? An experimental test in a wild passerine bird

A number of studies have suggested that avian brood size is individually optimized. Yet, optimal reproductive decisions likely vary owing to among-individual differences in environmental sensitivity. Specifically, ‘proactive’ individuals who do not track environmental changes may be less able to produce optimal brood sizes than ‘reactive’ individuals who have more precise local environmental knowledge. To test this, we quantified exploratory behaviour (a proxy for proactivity) in a great tit (Parus major) population, manipulated brood sizes (reduced, control, enlarged) and evaluated whether individuals of dissimilar coping style differed in their level of optimization. If reactive females behaved optimally, any deviation from their original brood size should lower fitness, whereas this should not be the case for proactive females. Reactive females indeed performed best at their natural brood size, whereas proactive females performed best when raising an enlarged brood. These findings imply that proactive females produced sub-optimal brood sizes. We speculate that proactive females might (i) take decisions based on biased perception of their environment, (ii) face energetic constraints in offspring production and/or (iii) be more willing to invest into current reproduction when given the option. Our findings provide experimental evidence for coping style-related differences in optimal reproductive decisions and life-history strategies.     

Concurrent Whole-Genome Haplotyping and Copy-Number Profiling of Single Cells

Methods for haplotyping and DNA copy-number typing of single cells are paramount for studying genomic heterogeneity and enabling genetic diagnosis. Before analyzing the DNA of a single cell by microarray or next-generation sequencing, a whole-genome amplification (WGA) process is required, but it substantially distorts the frequency and composition of the cell’s alleles. As a consequence, haplotyping methods suffer from error-prone discrete SNP genotypes (AA, AB, BB) and DNA copy-number profiling remains difficult because true DNA copy-number aberrations have to be discriminated from WGA artifacts. Here, we developed a single-cell genome analysis method that reconstructs genome-wide haplotype architectures as well as the copy-number and segregational origin of those haplotypes by employing phased parental genotypes and deciphering WGA-distorted SNP B-allele fractions via a process we coin haplarithmisis. We demonstrate that the method can be applied as a generic method for preimplantation genetic diagnosis on single cells biopsied from human embryos, enabling diagnosis of disease alleles genome wide as well as numerical and structural chromosomal anomalies. Moreover, meiotic segregation errors can be distinguished from mitotic ones.     

DNA lesion identity drives choice of damage tolerance pathway in murine cell chromosomes

DNA-damage tolerance (DDT) via translesion DNA synthesis (TLS) or homology-dependent repair (HDR) functions to bypass DNA lesions encountered during replication, and is critical for maintaining genome stability. Here, we present piggyBlock, a new chromosomal assay that, using piggyBac transposition of DNA containing a known lesion, measures the division of labor between the two DDT pathways. We show that in the absence of DNA damage response, tolerance of the most common sunlight-induced DNA lesion, TT-CPD, is achieved by TLS in mouse embryo fibroblasts. Meanwhile, BP-G, a major smoke-induced DNA lesion, is bypassed primarily by HDR, providing the first evidence for this mechanism being the main tolerance pathway for a biologically important lesion in a mammalian genome. We also show that, far from being a last-resort strategy as it is sometimes portrayed, TLS operates alongside nucleotide excision repair, handling 40% of TT-CPDs in repair-proficient cells. Finally, DDT acts in mouse embryonic stem cells, exhibiting the same pattern—mutagenic TLS included—despite the risk of propagating mutations along all cell lineages. The new method highlights the importance of HDR, and provides an effective tool for studying DDT in mammalian cells.     

Targeted purification development enabled by computational biophysical modeling

Chromatographic and non‐chromatographic purification of biopharmaceuticals depend on the interactions between protein molecules and a solid–liquid interface. These interactions are dominated by the protein–surface properties, which are a function of protein sequence, structure, and dynamics. In addition, protein–surface properties are critical for in vivo recognition and activation, thus, purification strategies should strive to preserve structural integrity and retain desired pharmacological efficacy. Other factors such as surface diffusion, pore diffusion, and film mass transfer can impact chromatographic separation and resin design. The key factors that impact non‐chromatographic separations (e.g., solubility, ligand affinity, charges and hydrophobic clusters, and molecular dynamics) are readily amenable to computational modeling and can enhance the understanding of protein chromatographic. Previously published studies have used computational methods such as quantitative structure–activity relationship (QSAR) or quantitative structure–property relationship (QSPR) to identify and rank order affinity ligands based on their potential to effectively bind and separate a desired biopharmaceutical from host cell protein (HCP) and other impurities. The challenge in the application of such an approach is to discern key yet subtle differences in ligands and proteins that influence biologics purification. Using a relatively small molecular weight protein (insulin), this research overcame limitations of previous modeling efforts by utilizing atomic level detail for the modeling of protein–ligand interactions, effectively leveraging and extending previous research on drug target discovery. These principles were applied to the purification of different commercially available insulin variants. The ability of these computational models to correlate directionally with empirical observation is demonstrated for several insulin systems over a range of purification challenges including resolution of subtle product variants (amino acid misincorporations). Broader application of this methodology in bioprocess development may enhance and speed the development of a robust purification platform. © 2014 American Institute of Chemical Engineers Biotechnol. Prog., 31:154–164, 2015     

Cognitive Functions in Elite and Sub-Elite Youth Soccer Players Aged 13 to 17 Years

Soccer players are required to anticipate and react continuously in a changing, relatively unpredictable situation in the field. Cognitive functions might be important to be successful in soccer. The current study investigated the relationship between cognitive functions and performance level in elite and sub-elite youth soccer players aged 13–17 years. A total of 47 elite youth soccer players (mean age 15.5 years, SD = 0.9) and 41 sub-elite youth soccer players (mean age 15.2 years, SD = 1.2) performed tasks for “higher-level” cognitive functions measuring working memory (i.e., Visual Memory Span), inhibitory control (i.e., Stop-Signal Task), cognitive flexibility (i.e., Trail Making Test), and metacognition (i.e., Delis-Kaplan Executive Function System Design Fluency Test). “Lower-level” cognitive processes, i.e., reaction time and visuo-perceptual abilities, were also measured with the previous tasks. ANOVA’s showed that elite players outscored sub-elite players at the “higher-level” cognitive tasks only, especially on metacognition (p < .05). Using stepwise discriminant analysis, 62.5% of subjects was correctly assigned to one of the groups based on their metacognition, inhibitory control and cognitive flexibility performance. Controlling for training hours and academic level, MANCOVA’s showed differences in favor of the elite youth soccer players on inhibitory control (p = .001), and cognitive flexibility (p = .042), but not on metacognition (p = .27). No differences were found concerning working memory nor the “lower-level” cognitive processes (p > .05). In conclusion, elite youth soccer players have better inhibitory control, cognitive flexibility, and especially metacognition than their sub-elite counterparts. However, when training hours are taken into account, differences between elite and sub-elite youth soccer players remain apparent on inhibitory control and cognitive flexibility in contrast to metacognition. This highlights the need for longitudinal studies to further investigate the importance of “higher-level” cognitive functions for talent identification, talent development and performance in soccer.     

A transport kinetic concept for ion uptake by plants

Summary A previously presented transport kinetic model for ion uptake by plants was tested by using data for copper uptake by barley grown in soil or water culture and corresponding data for copper concentration in the soil solution or culture solution. As no significant differences were obtained between experimentally determined values for copper uptake and those calculated by using the model, it was concluded that the experimental evidence was consistent with the proposed transport kinetic model. The model allows the Michaelis-Menten Constant of ion uptake and the Mean Maximal Rate of ion uptake to be calculated for various time intervals of the growth period of plants. The Michaelis-Menten Constant for copper uptake by barley grown in soil was the same as that for plants grown in water culture, provided that the soil solution and the water culture solution had the same chemical composition. The concentration of copper in the soil solution, at which the rate of copper uptake was zero, was 2–4 times larger than corresponding values obtained in water culture solution. re]19751028