Discovery of rare mutations in populations requires methods, such as TILLING (for Targeting Induced Local Lesions in Genomes), for processing and analyzing many individuals in parallel. Previous TILLING protocols employed enzymatic or physical discrimination of heteroduplexed from homoduplexed target DNA. Using mutant populations of rice (Oryza sativa) and wheat (Triticum durum), we developed a method based on Illumina sequencing of target genes amplified from multidimensionally pooled templates representing 768 individuals per experiment. Parallel processing of sequencing libraries was aided by unique tracer sequences and barcodes allowing flexibility in the number and pooling arrangement of targeted genes, species, and pooling scheme. Sequencing reads were processed and aligned to the reference to identify possible single-nucleotide changes, which were then evaluated for frequency, sequencing quality, intersection pattern in pools, and statistical relevance to produce a Bayesian score with an associated confidence threshold. Discovery was robust both in rice and wheat using either bidimensional or tridimensional pooling schemes. The method compared favorably with other molecular and computational approaches, providing high sensitivity and specificity.

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What is the effect of programming languages on software quality? This question has been a topic of much debate for a very long time. In this study, we gather a very large data set from GitHub (729 projects, 80 Million SLOC, 29,000 authors, 1.5 million commits, in 17 languages) in an attempt to shed some empirical light on this question. This reasonably large sample size allows us to use a mixed-methods approach, combining multiple regression modeling with visualization and text analytics, to study the effect of language features such as static v.s. dynamic typing, strong v.s. weak typing on software quality. By triangulating findings from different methods, and controlling for confounding effects such as team size, project size, and project history, we report that language design does have a significant, but modest effect on software quality. Most notably, it does appear that strong typing is modestly better than weak typing, and among functional languages, static typing is also somewhat better than dynamic typing. We also find that functional languages are somewhat better than procedural languages. It is worth noting that these modest effects arising from language design are overwhelmingly dominated by the process factors such as project size, team size, and commit size. However, we hasten to caution the reader that even these modest effects might quite possibly be due to other, intangible process factors, e.g., the preference of certain personality types for functional, static and strongly typed languages.

Commercial software project managers design project organizational structure carefully, mindful of available skills, division of labour, geographical boundaries, etc. These organizational "cathedrals" are to be contrasted with the "bazaarlike" nature of Open Source Software (OSS) Projects, which have no pre-designed organizational structure. Any structure that exists is dynamic, self-organizing, latent, and usually not explicitly stated. Still, in large, complex, successful, OSS projects, we do expect that subcommunities will form spontaneously within the developer teams. Studying these subcommunities, and their behavior can shed light on how successful OSS projects self-organize. This phenomenon could well hold important lessons for how commercial software teams might be organized. Building on known well-established techniques for detecting community structure in complex networks, we extract and study latent subcommunities from the email social network of several projects: Apache HTTPD, Python, PostgresSQL, Perl, and Apache ANT. We then validate them with software development activity history. Our results show that subcommunities do indeed spontaneously arise within these projects as the projects evolve. These subcommunities manifest most strongly in technical discussions, and are significantly connected with collaboration behaviour.

Angiosperm trees reorient their woody stems by asymmetrically producing a specialized xylem tissue, tension wood, which exerts a strong contractile force resulting in negative gravitropism of the stem. Here, we show, in Populus trees, that initial gravity perception and response occurs in specialized cells through sedimentation of starch-filled amyloplasts and relocalization of the auxin transport protein, PIN3. Gibberellic acid treatment stimulates the rate of tension wood formation and gravibending and enhances tissue-specific expression of an auxin-responsive reporter. Gravibending, maturation of contractile fibers, and gibberellic acid (GA) stimulation of tension wood formation are all sensitive to transcript levels of the Class I KNOX homeodomain transcription factor-encoding gene ARBORKNOX2 (ARK2). We generated genome-wide transcriptomes for trees in which gene expression was perturbed by gravistimulation, GA treatment, and modulation of ARK2 expression. These data were employed in computational analyses to model the transcriptional networks underlying wood formation, including identification and dissection of gene coexpression modules associated with wood phenotypes, GA response, and ARK2 binding to genes within modules. We propose a model for gravitropism in the woody stem in which the peripheral location of PIN3-expressing cells relative to the cambium results in auxin transport toward the cambium in the top of the stem, triggering tension wood formation, while transport away from the cambium in the bottom of the stem triggers opposite wood formation.

Abstract-StackOverflow is a popular on-line programming question and answer community providing its participants with rapid access to knowledge and expertise of their peers, especially benefitting coders. Despite the popularity of StackOverflow, its role in the work cycle of open-source developers is yet to be understood: on the one hand, participation in it has the potential to increase the knowledge of individual developers thus improving and speeding up the development process. On the other hand, participation in StackOverflow may interrupt the regular working rhythm of the developer, hence also possibly slow down the development process.In this paper we investigate the interplay between StackOverflow activities and the development process, reflected by code changes committed to the largest social coding repository, GitHub. Our study shows that active GitHub committers ask fewer questions and provide more answers than others. Moreover, we observe that active StackOverflow askers distribute their work in a less uniform way than developers that do not ask questions. Finally, we show that despite the interruptions incurred, the StackOverflow activity rate correlates with the code changing activity in GitHub.

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