540 research outputs found
Molecular evolution of genes in avian genomes
Nam K, Mugal C, Nabholz B, et al. Molecular evolution of genes in avian genomes. Genome Biology. 2010;11(6): R68.Background: Obtaining a draft genome sequence of the zebra finch (Taeniopygia guttata), the second bird genome to be sequenced, provides the necessary resource for whole-genome comparative analysis of gene sequence evolution in a non-mammalian vertebrate lineage. To analyze basic molecular evolutionary processes during avian evolution, and to contrast these with the situation in mammals, we aligned the protein-coding sequences of 8,384 1:1 orthologs of chicken, zebra finch, a lizard and three mammalian species. Results: We found clear differences in the substitution rate at fourfold degenerate sites, being lowest in the ancestral bird lineage, intermediate in the chicken lineage and highest in the zebra finch lineage, possibly reflecting differences in generation time. We identified positively selected and/or rapidly evolving genes in avian lineages and found an overrepresentation of several functional classes, including anion transporter activity, calcium ion binding, cell adhesion and microtubule cytoskeleton. Conclusions: Focusing specifically on genes of neurological interest and genes differentially expressed in the unique vocal control nuclei of the songbird brain, we find a number of positively selected genes, including synaptic receptors. We found no evidence that selection for beneficial alleles is more efficient in regions of high recombination; in fact, there was a weak yet significant negative correlation between ω and recombination rate, which is in the direction predicted by the Hill-Robertson effect if slightly deleterious mutations contribute to protein evolution. These findings set the stage for studies of functional genetics of avian genes
Incorporation of feedback during beat synchronization is an index of neural maturation and reading skills
Speech communication involves integration and coordination of sensory perception and motor production, requiring precise temporal coupling. Beat synchronization, the coordination of movement with a pacing sound, can be used as an index of this sensorimotor timing. We assessed adolescents’ synchronization and capacity to correct asynchronies when given online visual feedback. Variability of synchronization while receiving feedback predicted phonological memory and reading sub-skills, as well as maturation of cortical auditory processing; less variable synchronization during the presence of feedback tracked with maturation of cortical processing of sound onsets and resting gamma activity. We suggest the ability to incorporate feedback during synchronization is an index of intentional, multimodal timing-based integration in the maturing adolescent brain. Precision of temporal coding across modalities is important for speech processing and literacy skills that rely on dynamic interactions with sound. Synchronization employing feedback may prove useful as a remedial strategy for individuals who struggle with timing-based language learning impairments
Utilizing plant genetic resources for pre-breeding of water-efficient sorghum: genetics of the limited transpiration trait
Includes bibliographical references.2022 Fall.Shifting precipitation patterns driven by the changing climate threaten productivity of dryland agricultural systems. Increasing the efficiency of water use by crops grown in dryland regions, such as sorghum (Sorghum bicolor), is a target for plant breeding to address this issue. c variants conferring efficient water use in sorghum may be found within collections of plant genetic resources (PGR). However, tropical sorghum PGR require adaptation to the target temperate environment to begin the pre-breeding trait discovery process. The landmark Sorghum Conversion Program unlocked diverse sorghum genetics for temperate breeding by adapting tropical African lines to temperate height and maturity standards. In the U.S. Sorghum Belt, spanning South Dakota to central Texas, the limited transpiration (LT) trait could provide growers a 5% yield increase in water-limited conditions with high vapor pressure deficit (VPD) according to crop modeling. To transfer the LT trait into commercial breeding programs, an elite donor line must be developed. Characterizing the genetic architecture of LT informs markers and breeding strategy for development of an elite donor. To characterize the genetic architecture of LT, two biparental recombinant inbred line (RIL) mapping families were developed from crossing putative LT parents SC979 and BTx2752 by putative non-LT parent RTx430. For this study, the families were grown together as a mapping population in three locations (continental-humid eastern Kansas, semi-arid western Kansas, and semi-arid Colorado) in one year. The families were phenotyped for the LT trait using UAS- collected thermal imaging and canopy temperature as a proxy. The families were initially designed with the goal of controlling phenotypic covariates of canopy temperature associated with height and flowering time, like neighbor-shading and artifactual temperature inflation related to panicle imaging. To test whether the family design controlled for height and flowering time covariates, the populations were phenotyped for both traits. High broad-sense heritability (H2) > 0.86 for all traits and families across locations indicates that the traits are not fixed. However, phenotypic distributions reveal that most lines are within an agronomically-relevant range that limits confounding covariates. Using DArTseq-LD genotyping data, GWAS analyses of height and flowering time reveal putatively significant marker-trait associations (MTA) with known loci underlying height and maturity in sorghum. These results collectively indicate that, while genetic variation for height and flowering exist in the LT mapping families, the resulting phenotypes are homogeneous enough to be suitable for LT genetic mapping. To test hypotheses on the monogenic, oligogenic, or polygenic architecture of the LT trait, canopy temperature data collected by the UAS-thermal imaging missions was used. Non-zero H2 of canopy temperature in most location-timepoints indicates genetic variation is present for LT in the population. Continuous phenotypic distributions imply a quantitative architecture. GWAS analyses revealed moderate marker-trait association peaks visible within timepoints and across locations, indicating oligogenic architecture of LT. Some of those peaks also colocalize with sorghum homologs of aquaporin genes in Arabidopsis thaliana, suggesting that aquaporin variation could be a molecular basis underlying the trait. These results provide a basis for marker-assisted selection in developing an LT donor line
Deepr: A Convolutional Net for Medical Records
Feature engineering remains a major bottleneck when creating predictive
systems from electronic medical records. At present, an important missing
element is detecting predictive regular clinical motifs from irregular episodic
records. We present Deepr (short for Deep record), a new end-to-end deep
learning system that learns to extract features from medical records and
predicts future risk automatically. Deepr transforms a record into a sequence
of discrete elements separated by coded time gaps and hospital transfers. On
top of the sequence is a convolutional neural net that detects and combines
predictive local clinical motifs to stratify the risk. Deepr permits
transparent inspection and visualization of its inner working. We validate
Deepr on hospital data to predict unplanned readmission after discharge. Deepr
achieves superior accuracy compared to traditional techniques, detects
meaningful clinical motifs, and uncovers the underlying structure of the
disease and intervention space
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Integrative analysis of the inter-tumoral heterogeneity of triple-negative breast cancer.
Triple-negative breast cancers (TNBC) lack estrogen and progesterone receptors and HER2 amplification, and are resistant to therapies that target these receptors. Tumors from TNBC patients are heterogeneous based on genetic variations, tumor histology, and clinical outcomes. We used high throughput genomic data for TNBC patients (n = 137) from TCGA to characterize inter-tumor heterogeneity. Similarity network fusion (SNF)-based integrative clustering combining gene expression, miRNA expression, and copy number variation, revealed three distinct patient clusters. Integrating multiple types of data resulted in more distinct clusters than analyses with a single datatype. Whereas most TNBCs are classified by PAM50 as basal subtype, one of the clusters was enriched in the non-basal PAM50 subtypes, exhibited more aggressive clinical features and had a distinctive signature of oncogenic mutations, miRNAs and expressed genes. Our analyses provide a new classification scheme for TNBC based on multiple omics datasets and provide insight into molecular features that underlie TNBC heterogeneity
Open source software ecosystems : a systematic mapping
Context: Open source software (OSS) and software ecosystems (SECOs) are two consolidated research areas in software engineering. OSS influences the way organizations develop, acquire, use and commercialize software. SECOs have emerged as a paradigm to understand dynamics and heterogeneity in collaborative software development. For this reason, SECOs appear as a valid instrument to analyze OSS systems. However, there are few studies that blend both topics together. Objective: The purpose of this study is to evaluate the current state of the art in OSS ecosystems (OSSECOs) research, specifically: (a) what the most relevant definitions related to OSSECOs are; (b) what the particularities of this type of SECO are; and (c) how the knowledge about OSSECO is represented. Method: We conducted a systematic mapping following recommended practices. We applied automatic and manual searches on different sources and used a rigorous method to elicit the keywords from the research questions and selection criteria to retrieve the final papers. As a result, 82 papers were selected and evaluated. Threats to validity were identified and mitigated whenever possible. Results: The analysis allowed us to answer the research questions. Most notably, we did the following: (a) identified 64 terms related to the OSSECO and arranged them into a taxonomy; (b) built a genealogical tree to understand the genesis of the OSSECO term from related definitions; (c) analyzed the available definitions of SECO in the context of OSS; and (d) classified the existing modelling and analysis techniques of OSSECOs. Conclusion: As a summary of the systematic mapping, we conclude that existing research on several topics related to OSSECOs is still scarce (e.g., modelling and analysis techniques, quality models, standard definitions, etc.). This situation calls for further investigation efforts on how organizations and OSS communities actually understand OSSECOs.Peer ReviewedPostprint (author's final draft
FLNeRF: 3D Facial Landmarks Estimation in Neural Radiance Fields
This paper presents the first significant work on directly predicting 3D face
landmarks on neural radiance fields (NeRFs), without using intermediate
representations such as 2D images, depth maps, or point clouds. Our 3D
coarse-to-fine Face Landmarks NeRF (FLNeRF) model efficiently samples from the
NeRF on the whole face with individual facial features for accurate landmarks.
To mitigate the limited number of facial expressions in the available data,
local and non-linear NeRF warp is applied at facial features in fine scale to
simulate large emotions range, including exaggerated facial expressions (e.g.,
cheek blowing, wide opening mouth, eye blinking), for training FLNeRF. With
such expression augmentation, our model can predict 3D landmarks not limited to
the 20 discrete expressions given in the data. Robust 3D NeRF facial landmarks
contribute to many downstream tasks. As an example, we modify MoFaNeRF to
enable high-quality face editing and swapping using face landmarks on NeRF,
allowing more direct control and wider range of complex expressions.
Experiments show that the improved model using landmarks achieves comparable to
better results.Comment: Hao Zhang and Tianyuan Dai contributed equally. Project website:
https://github.com/ZHANG1023/FLNeR
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