Quantification of Cas9 binding and cleavage across diverse guide sequences maps landscapes of target engagement

The RNA-guided nuclease Cas9 has unlocked powerful methods for perturbing both the genome through targeted DNA cleavage and the regulome through targeted DNA binding, but limited biochemical data have hampered efforts to quantitatively model sequence perturbation of target binding and cleavage across diverse guide sequences. We present scalable, sequencing-based platforms for high-throughput filter binding and cleavage and then perform 62,444 quantitative binding and cleavage assays on 35,047 on- and off-target DNA sequences across 90 Cas9 ribonucleoproteins (RNPs) loaded with distinct guide RNAs. We observe that binding and cleavage efficacy, as well as specificity, vary substantially across RNPs; canonically studied guides often have atypically high specificity; sequence context surrounding the target modulates Cas9 on-rate; and Cas9 RNPs may sequester targets in nonproductive states that contribute to “proofreading” capability. Lastly, we distill our findings into an interpretable biophysical model that predicts changes in binding and cleavage for diverse target sequence perturbations.

Splicing at the phase-separated nuclear speckle interface: a model

Phase-separated membraneless bodies play important roles in nucleic acid biology. While current models for the roles of phase separation largely focus on the compartmentalization of constituent proteins, we reason that other properties of phase separation may play functional roles. Specifically, we propose that interfaces of phase-separated membraneless bodies could have functional roles in spatially organizing biochemical reactions. Here we propose such a model for the nuclear speckle, a membraneless body implicated in RNA splicing. In our model, sequence-dependent RNA positioning along the nuclear speckle interface coordinates RNA splicing. Our model asserts that exons are preferentially sequestered into nuclear speckles through binding by SR proteins, while introns are excluded through binding by nucleoplasmic hnRNP proteins. As a result, splice sites at exon-intron boundaries are preferentially positioned at nuclear speckle interfaces. This positioning exposes splice sites to interface-localized spliceosomes, enabling the subsequent splicing reaction. Our model provides a simple mechanism that seamlessly explains much of the complex logic of splicing. This logic includes experimental results such as the antagonistic duality between splicing factors, the position dependence of splicing sequence motifs, and the collective contribution of many motifs to splicing decisions. Similar functional roles for phase-separated interfaces may exist for other membraneless bodies.

IMPLEMENTASI MODEL PEMBELAJARAN HABIT FORMING DALAM PEMBENTUKAN KEPRIBADIAN HOLISTIC MELALUI PEMBELAJARAN AQIDAH AKHLAK DI SEKOLAH ADIWIYATA MI AL-FALAH KUNCUNG BANYUARANG NGORO JOMBANG

School is one of the educational institutions that organizes the teaching and learning process to guide, educate, train and develop student’s abilities to achieve educational goals, including human character at MI Al-Falah Kuncung there is a habit, especially in carrying out daily habits.The focus of research on this thesis is as follows: 1) How is the learning of aqidah akhlak in grade IV at the adiwiyata school MI Al-Falah Kuncung Banyuarang Ngoro Jombang?, 2) How is the implementation of the habit forming learning model in the adiwiyata school MI Al-Falah Kuncung Banyuarang Ngoro Jombang?, 3) What is the holistic personality of the fourth grade personality of the fourth grade students at MI Al-Falah Kuncung Banyuarang Ngoro Jombang adiwiyata school?The approach in this research uses a qualitative approach with a descriptive type. The research setting took place at MI Al-Falah Kuncung Banyuarang Ngoro Jombang. Meanwhile the data sources are teachers of aqidah morals, classroom teachers, students, and directors. Way of unifying data using interviews, observation, and archiving.The research results obtained by the researcher are as follows: 1) learning aqidah akhlak is carried out by applying a habit that is in accordance with the personality that you want to build on learning aqidah morals, namely by opening greetings, greeting students at the core of reading, listening, and discussing. After that, the cover held a reflection and concluded together, 2) the application of the habit forming learning model starting from (the habit formation model sequence) the steps of habit forming in students habits are carried out continuously and someone or role model, and 3) a holistic personality what is seen in grade IV students is that they are able to apply moral behavior, and also position their behavior as a student, but they have not been able to control their own behavior, this can be seen from the attitudes of some students when learning aqidah morals takes place they do not concentrate and tend not to pay attention to the teacher.

Structure, membrane topology and influence of cholesterol of the membrane proximal region: transmembrane helical anchor sequence of gp41 from HIV

During the first steps of HIV infection the Env subunit gp41 is thought to establish contact between the membranes and to be the main driver of fusion. Here we investigated in liquid crystalline membranes the structure and cholesterol recognition of constructs made of a gp41 external region carrying a cholesterol recognition amino acid consensus (CRAC) motif and a hydrophobic membrane anchoring sequence. CD- und ATR-FTIR spectroscopies indicate that the constructs adopt a high degree of helical secondary structure in membrane environments. Furthermore, 15N and 2H solid-state NMR spectra of gp41 polypeptides reconstituted into uniaxially oriented bilayers agree with the CRAC domain being an extension of the transmembrane helix. Upon addition of cholesterol the CRAC NMR spectra remain largely unaffected when being associated with the native gp41 transmembrane sequence but its topology changes when anchored in the membrane by a hydrophobic model sequence. The 2H solid-state NMR spectra of deuterated cholesterol are indicative of a stronger influence of the model sequence on this lipid when compared to the native gp41 sequence. These observations are suggestive of a strong coupling between the transmembrane and the membrane proximal region of gp41 possibly enforced by oligomerization of the transmembrane helical region.

Quantification of Cas9 binding and cleavage across diverse guide sequences maps landscapes of target engagement

The RNA-guided nuclease Cas9 has unlocked powerful methods for perturbing both the genome through targeted DNA cleavage and the regulome through targeted DNA binding, but limited biochemical data has hampered efforts to quantitatively model sequence perturbation of target binding and cleavage across diverse guide sequences. We present scalable, sequencing-based platforms for high-throughput filter binding and cleavage, then perform 62,444 quantitative binding and cleavage assays on 35,047 on- and off-target DNA sequences across 90 Cas9 ribonucleoproteins (RNPs) loaded with distinct guide RNAs. We observe that binding and cleavage efficacy, as well as specificity, vary substantially across RNPs; canonically studied guides often have atypically high specificity; sequence context surrounding the target significantly influences Cas9 on-rate; and Cas9 RNPs may sequester targets in nonproductive states that contribute to “proofreading” capability. Finally, we distill our findings into an interpretable biophysical model that predicts changes in binding and cleavage for diverse target sequence perturbations.

Multinomial Convolutions for Joint Modeling of Sequence Motifs and Enhancer Activities

Massively parallel reporter assays (MPRAs) have enabled the study of transcriptional regulatory mechanisms at an unprecedented scale and with high quantitative resolution. However, this realm lacks models that can discover sequence-specific signals de novo from the data and integrate them in a mechanistic way. We present MuSeAM (Multinomial CNNs for Sequence Activity Modeling), a convolutional neural network that overcomes this gap. MuSeAM utilizes multinomial convolutions that directly model sequence-specific motifs of protein-DNA binding. We demonstrate that MuSeAM fits MPRA data with high accuracy and generalizes over other tasks such as predicting chromatin accessibility and prioritizing potentially functional variants.

How sequence populations persist inside a genome

Compared to their eukaryotic counterparts, bacterial genomes are small and contain extremely tightly packed genes. Therefore, discovering a large number of short repetitive sequences in the genomes of Pseudomonads and Enterobacteria is unexpected. These sequences can independently replicate in the host genome and form populations that persist for millions of years. Here we model the interactions of intragenomic sequence populations with the bacterial host. In a simple model, sequence populations either expand until they drive the host to extinction or the sequence population gets purged from the genome. Including horizontal gene transfer does not change the qualitative outcome of the model and leads to the extinction of the sequence population. However, a sequence population can be stably maintained, if each sequence provides a benefit that decreases with increasing sequence population size. But concurrently, the replication of the sequence population needs to be costly to the host. Surprisingly, in regimes where horizontal gene transfer plays a role, the benefit conferred by the sequence population does not have to exceed the damage it causes. Together, our analyses provide a plausible scenario for the persistence of sequence populations in bacterial genomes. More importantly, we hypothesize a limited biologically relevant parameter range, which can be tested in future experiments.

Multi Respon Ranking Pada Percakapan Layanan Travel Berdasarkan Riwayat Obrolan

Membangun sebuah chatbot tidak lepas dari basis pengetahuan. Basis pengetahuan bisa diperoleh dari data yang telah diberi label oleh pengembang, dokumen yang telah di konversi menjadi pre-processing data, atau informasi yang diambil dari media sosial. Dalam hal ini, data yang digunakan sebagai pengetahuan adalah riwayat obrolan. Dialam riwayat obrolan tersebut tentu banyak sekali variasi jawaban dan menungkinkan satu pertanyaan menimbulkan banyak jawaban. Untuk mengatasi multi respon tersebut maka dibuatlah pemeringaktan respon. Adanya pemeringkatan, tentu respon yang diinginkan oleh pengguna akan lebih sesuai. Tantangan dalam pemeringkatan adalah bagaimana mendapatkan inti dari sebuah pertanyaan dan menemukan pasangan tanya jawab dari data. Hal tersebut bisa diselesaikan dengan model sequence to sequence. Namun, permasalahan yang akan muncul adalah konsistensi jawaban. Adanya banyak riwayat obrolan dari layanan travel tentu menimbulkan banyak jawaban mesi inti dari pertanyaan adalah sama. Untuk itu Algoritma CNN sebagai solusi untuk permasalahan tersebut. Penelitian ini menggunakan convolutional sequence to sequence yang akan diterapkan untuk respon ranking. Kami memandingkan efisiensi dari model ini. Dengan melakukan perbandingan, model ini menunjukan hasil akurasi sebesar 86.7%