Phylogeny and chloroplast evolution in Brassicaceae

Brassicaceae is a large family of flowering plants, characterized by cruciform corolla, tetradynamous stamen and capsular fruit. In light of the important economic and scientific values of Brassicaceae, many phylogenetic and systematic studies were carried out. One recent and important phylogenetic analysis revealed three major lineages (I, II and III), however, classification at different taxonomic levels (tribe, genus, and species) remained problematic and evolutionary relationships among and within these lineages were still largely unclear. This is partly due to the fact that the past studies lacked information, as they mainly utilized the morphological data, nuclear DNA, partial chloroplast (cp) genes and so on. Nowadays, next generation sequencing (NGS) technology provides the possibility to make use of big data in phylogeny and evolutionary studies. Thus, we sequenced the chloroplast genomes of 80 representative species, using additional 15 reference chloroplast genomes from the NCBI database, and carried out both the phylogenetic reconstruction and the study of protein coding genes evolution in this novel dataset with different methods. Several novel results were obtained. 1 Successful application of NGS technology in chloroplast genome sequencing. During the final assembly, I could reconstruct full chloroplast genomes and the structure maps for 14 out of 80 sampled species, while the remaining were assembled nearly completely with only few gaps remaining. 2 Characterization of chloroplast genome structure. Gene number and order, single sequence repeat (SSR) as well as variety and distribution of large repeat sequence were characterized. 3 The difference of codon usage frequency was calculated between Cardamine resedifolia and Cardamine impatiens. Twelve genes with signatures of positive selection were identified at a family-wide level. 4 Three major lineages (I – III) were confirmed with high support values. Besides, the positions of various tribes were reclassified. Relationships among and within these lineages were highly resolved and supported in the final tree. Most of the tribes in the analyses were inferred to be monophyletic, only Thlaspideae was paraphyletic. Anastaticeae was for the first time classified into position of expanded lineage II, and position of tribe Lepidieae was delimited with relatively low support values in the final phylogenetic tree. This study was a new and successful application of NGS in large-scale Brassicaceae phylogeny and evolution, which offered the chance to look in details of the structural and functional features of the chloroplast genome. These results provided a paradigm on how to proceed towards the full elucidation of the evolutionary relationships among various biological species in the tree of life

FunCodec: A Fundamental, Reproducible and Integrable Open-source Toolkit for Neural Speech Codec

This paper presents FunCodec, a fundamental neural speech codec toolkit, which is an extension of the open-source speech processing toolkit FunASR. FunCodec provides reproducible training recipes and inference scripts for the latest neural speech codec models, such as SoundStream and Encodec. Thanks to the unified design with FunASR, FunCodec can be easily integrated into downstream tasks, such as speech recognition. Along with FunCodec, pre-trained models are also provided, which can be used for academic or generalized purposes. Based on the toolkit, we further propose the frequency-domain codec models, FreqCodec, which can achieve comparable speech quality with much lower computation and parameter complexity. Experimental results show that, under the same compression ratio, FunCodec can achieve better reconstruction quality compared with other toolkits and released models. We also demonstrate that the pre-trained models are suitable for downstream tasks, including automatic speech recognition and personalized text-to-speech synthesis. This toolkit is publicly available at https://github.com/alibaba-damo-academy/FunCodec.Comment: 5 pages, 3 figures, submitted to ICASSP 202

Plastome organization and evolution of chloroplast genes in Cardamine species adapted to contrasting habitats

© 2015 Hu et al.; licensee BioMed Central. Background: Plastid genomes, also known as plastomes, are shaped by the selective forces acting on the fundamental cellular functions they code for and thus they are expected to preserve signatures of the adaptive path undertaken by different plant species during evolution. To identify molecular signatures of positive selection associated to adaptation to contrasting ecological niches, we sequenced with Solexa technology the plastomes of two congeneric Brassicaceae species with different habitat preference, Cardamine resedifolia and Cardamine impatiens. Results: Following in-depth characterization of plastome organization, repeat patterns and gene space, the comparison of the newly sequenced plastomes between each other and with 15 fully sequenced Brassicaceae plastomes publically available in GenBank uncovered dynamic variation of the IR boundaries in the Cardamine lineage. We further detected signatures of positive selection in ten of the 75 protein-coding genes of the examined plastomes, identifying a range of chloroplast functions putatively involved in adaptive processes within the family. For instance, the three residues found to be under positive selection in RUBISCO could possibly be involved in the modulation of RUBISCO aggregation/activation and enzymatic specificty in Brassicaceae. In addition, our results points to differential evolutionary rates in Cardamine plastomes. Conclusions: Overall our results support the existence of wider signatures of positive selection in the plastome of C. resedifolia, possibly as a consequence of adaptation to high altitude environments. We further provide a first characterization of the selective patterns shaping the Brassicaceae plastomes, which could help elucidate the driving forces underlying adaptation and evolution in this important plant family

A Transfer Learning Approach for Malignant Prostate Lesion Detection on Multiparametric MRI

Purpose: In prostate focal therapy, it is important to accurately localize malignant lesions in order to increase biological effect of the tumor region while achieving a reduction in dose to noncancerous tissue. In this work, we proposed a transfer learning–based deep learning approach, for classification of prostate lesions in multiparametric magnetic resonance imaging images. Methods: Magnetic resonance imaging images were preprocessed to remove bias artifact and normalize the data. Two state-of-the-art deep convolutional neural network models, InceptionV3 and VGG-16, were pretrained on ImageNet data set and retuned on the multiparametric magnetic resonance imaging data set. As lesion appearances differ by the prostate zone that it resides in, separate models were trained. Ensembling was performed on each prostate zone to improve area under the curve. In addition, the predictions from lesions on each prostate zone were scaled separately to increase the area under the curve for all lesions combined. Results: The models were tuned to produce the highest area under the curve on validation data set. When it was applied to the unseen test data set, the transferred InceptionV3 model achieved an area under the curve of 0.81 and the transferred VGG-16 model achieved an area under the curve of 0.83. This was the third best score among the 72 methods from 33 participating groups in ProstateX competition. Conclusion: The transfer learning approach is a promising method for prostate cancer detection on multiparametric magnetic resonance imaging images. Features learned from ImageNet data set can be useful for medical images

Impact of Uniaxial Pressure on Structural and Magnetic Phase Transitions in Electron-Doped Iron Pnictides

We use neutron resonance spin echo and Larmor diffraction to study the effect of uniaxial pressure on the tetragonal-to-orthorhombic structural ($T_s$) and antiferromagnetic (AF) phase transitions in iron pnictides BaFe$_{2-x}$Ni$_{x}$As$_{2}$ ($x=0,0.03,0.12$), SrFe$_{1.97}$Ni$_{0.03}$As$_2$, and BaFe$_2$(As$_{0.7}$P$_{0.3}$)$_2$. In antiferromagnetically ordered BaFe$_{2-x}$Ni$_{x}$As$_{2}$ and SrFe$_{1.97}$Ni$_{0.03}$As$_2$ with $T_N$ and $T_s$ ($T_N\leq T_s$), a uniaxial pressure necessary to detwin the sample also increases $T_N$, smears out the structural transition, and induces an orthorhombic lattice distortion at all temperatures. By comparing temperature and doping dependence of the pressure induced lattice parameter changes with the elastoresistance and nematic susceptibility obtained from transport and ultrasonic measurements, we conclude that the in-plane resistivity anisotropy found in the paramagnetic state of electron underdoped iron pnictides depends sensitively on the nature of the magnetic phase transition and a strong coupling between the uniaxial pressure induced lattice distortion and electronic nematic susceptibility.Comment: 18 pages, 15 figure

LASER: Light, Accurate Sharing dEtection and Repair

Contention for shared memory, in the forms of true sharing and false sharing, is a challenging performance bug to discover and to repair. Understanding cache contention requires global knowledge of the program\u27s actual sharing behavior, and can even arise invisibly in the program due to the opaque decisions of the memory allocator. Previous schemes have focused only on false sharing, and impose significant performance penalties or require non-trivial alterations to the operating system or runtime system environment. This paper presents the Light, Accurate Sharing dEtection and Repair (LASER) system, which leverages new performance counter capabilities available on Intel\u27s Haswell architecture that identify the source of expensive cache coherence events. Using records of these events generated by the hardware, we build a system for online contention detection and repair that operates with low performance overhead and does not require any invasive program, compiler or operating system changes. Our experiments show that LASER imposes just 2% average runtime overhead on the Phoenix, Parsec and Splash2x benchmarks. LASER can automatically improve the performance of programs by up to 19% on commodity hardware