STARR مؤسسة جائزة (MQZ)، NIH منحة ES017166 (MQZ)، NSF منحة DMS0906593 (HX).

1. إعداد ملفات الإدخال لتحليل BCP <ol style=";text-align:right;direction:rtl"><li style=";text-align:right;direction:rtl"> محاذاة قصيرة التسلسل يقرأ المنتجة من أشواط (رقاقة والمكتبات المدخلات) إلى الجينوم مرجعية مناسبة باستخدام المحاذاة المفضل قراءة قصيرة البرمجيات. ينبغي تحويل المواقع تعيينها إلى 6 بيانات العمود الموسعة متصفح (BED) شكل 13 (UCSC متصفح الجينوم، <a href="http://genome.ucsc.edu/" target="_blank">http://genome.ucsc.edu/</a> )، وهو خط المفصول في قراءة معين مما يدل على كروموسوم معين، تبدأ الموقف (0-إلى)، نهاية الموقف (نصف مفتوحة)، وقراءة الاسم ونقاط (اختياري)، وحبلا. </li></ol> 2A. نشر مقروءة الملامح: تشيب تجهيزها لقراءة كثافات الكشف عن اليورانيوم في جزر البيانات منتشر <ol style=";text-align:right;direction:rtl"><li style=";text-align:right;direction:rtl"> تمديد رقاقة والمواقع الإدخال تعيينها إلى طول القطعة محددة سلفا، أي. حجم جزء استهدفت خلال عملية الهضم الانزيم أو sonication من الحمض النووي، وعادة حوالي 200 سنة مضت. التهم هي جزء ثم aggregaتيد في صناديق المجاورة. افتراضيا، يتم تعيين حجم بن لطول جزء تقدر ب 200 BP. </li><li style=";text-align:right;direction:rtl"> إن أي تغيير محتمل في نقاط مجموعة من صناديق متطابقة مع قراءة معظم التهم سقوط المحتمل في الحدود الخارجية أكثر. وبناء عليه، فإنه ليس واردا أن نقطة التغيير سوف يحدث في الحدود الداخلية بين اثنين من صناديق مع التهم قراءة نفسه. لذلك، مجموعة صناديق المجاورة، مع مطابقة يقرأ في بن، في كتلة واحدة، أي. bedGraph شكل 13. </li></ol> 2B. منقط ملامح القراءة: رقاقة تجهيزها وملفات الإدخال BED لكشف البيانات في قمم المنقط <ol style=";text-align:right;direction:rtl"><li style=";text-align:right;direction:rtl"> تداخل الكلي ليقرأ المعالج حبلا زائد وناقص يقرأ بشكل منفصل. ينبغي أن حبلا محددة كثافة قراءة تشكيل الملف الشخصي ذات النسقين من قمم زائد وناقص. بالإضافة إلى اختيار أزواج / ناقص من قمم معظم المخصب واستخدام المسافة بين القمة على أنها تقدير لمكتبة طول القطعة. </li><li style=";text-align:right;direction:rtl"> تحويل شريحة والمدخلات يقرأ نصف جنيه جزءngth إلى المركز وإعادة حساب الكثافة للقراءة بالإضافة إلى تحول ودمج وناقص يقرأ حبلا. اعتمد هذه المنهجية لتقدير طول جزء من تشانغ، وآخرون. 3. ينبغي تجميع مواقف متطابقة مع دمج التهم إلى كتل، على غرار الخطوة 2a.2. </li></ol> 3. تقدير متوسط ​​الخلفي كلمة كثافة استخدام كل كتلة لدينا تقريب BCMIX <ol style=";text-align:right;direction:rtl"><li style=";text-align:right;direction:rtl"> وعلى غرار كثافة قراءة كل كتلة وتوزيع بواسون، تغييرنقاط POI (θ ر)، مع معلمة يعني بعد خليط من توزيعات غاما، Γ (α، β)، واحتمال مسبقة من نقطة التغيير التي تحدث في أي كتلة الحدود ع. تكييف تغييرنقاط POI (θ ر) على G (α، β) يجعل نموذج فعال لHMM الدولة لانهائية. تقدير فرط المعلمات، α، β، و ف، وذلك باستخدام أقصى احتمال الخلفي. </li><li style=";text-align:right;direction:rtl"> حساب تقديرات بايز صراحة عنكل كتلة، ر θ، وE (θ ر | γ Z). استبدال المستهلكة التقليدية ولكن الوقت إلى الأمام والخلف الفلاتر غالبا ما تستخدم في HMMs، مع تقريب التعقيد أكثر كفاءة خليط حسابيا لتقدير وسائل يحدها الخلفي، θ ج. وسوف تنتج وسائل الخلفي يكون &quot;ممهدة&quot; في ملف تعريف تقريبي المستمر piecewise ولذلك يجب كتل مع ج، θ متطابقة، ومنعت كذلك مع الحدود تحديث الإحداثيات. </li></ol> 4A. نشر مقروءة الملامح: ما بعد العملية يعني الخلفي إلى قطاعات لتخصيب منتشر <ol style=";text-align:right;direction:rtl"><li style=";text-align:right;direction:rtl"> استخدام عدد من المدخلات يقرأ في كل كتلة جديدة ج θ، حيث وصل سعر الخلفية، تغييرنقاط POI (λ أ) وتحديد تخصيب باستخدام اختبار فرضية بسيطة، تنبني على ما إذا كان يعني رقاقة الخلفي، θ ج، يتجاوز بعض δ العتبة. ال 90 &lt;/ سوب&gt;-quantile هو د الافتراضي وغير مناسبة في معظم الحالات. </li><li style=";text-align:right;direction:rtl"> دمج المجاورة θ ج الكتل التي يتجاوز تخصيب في منطقة واحدة ودمج التقرير في شكل إحداثيات BED بسيطة. بدلا من ذلك، يمكن للمرء أن تقرير θ ج لكل كتلة في شكل bedGraph للحفاظ على تفاصيل عالية الدقة للتقديرات الكثافة قراءة. </li></ol> 4B. منقط مقروءة الملامح: ما بعد العملية يعني الخلفي إلى المرشحين الذروة <ol style=";text-align:right;direction:rtl"><li style=";text-align:right;direction:rtl"> تحديد النسبة الخلفية، تغييرنقاط POI (λ أ)، ومتوسط ​​قراءة جميع التهم الموجهة إليه (γ 2) وتحديد جميع الكتل التي تتجاوز عتبة، د. ومن المتوقع منذ قمم منقط إلى أن تكون أكثر بكثير المخصب، يتم تعيين الافتراضي إلى δ-quantile ال 99 من النقاط المهمة (λ أ). </li><li style=";text-align:right;direction:rtl"> تعيين كتلة (ج) مع θ القصوى كمرشح قمة الذروة وتجاور كتل المرافقة التي تشترك في دين قراءة مماثلةsity (± 1 قراءة الاعتماد للسماح اختلاف طفيف). يتم تعريف هذه المنطقة ملاصقة كموقع مرشح ملزمة. </li><li style=";text-align:right;direction:rtl"> حساب λ (2)، التهم متوسط ​​قراءة في موقع المرشح المعالج اختبار الفرضية الملزمة وهذه الخلفية المدخلات مقابل كانت فرضية العدم، H 0، هو أن λ 1 ≥ λ (2) ورفض H 0 استنادا عتبة ف القيمة. قمم مرشح الإخراج في تنسيق BED. </li></ol>

<ol>
	<li>Park, P. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=ChIP-seq:+advantages+and+challenges+of+a+maturing+technology.">ChIP-seq: advantages and challenges of a maturing technology.</a> Nat. Rev. Genet. 10, 669-680 (2009).</li><li>Barski, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=High-resolution+profiling+of+histone+methylations+in+the+human+genome.">High-resolution profiling of histone methylations in the human genome.</a> Cell. 129, 823-837 (2007).</li><li>Zhang, Y., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Model-based+Analysis+of+ChIP-Seq+(MACS).">Model-based Analysis of ChIP-Seq (MACS).</a> Genome Biol. 9, R137 (2008).</li><li>Zang, C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+clustering+approach+for+identification+of+enriched+domains+from+histone+modification+ChIP-Seq+data.">A clustering approach for identification of enriched domains from histone modification ChIP-Seq data.</a> Bioinformatics. 25, 1952-1958 (2009).</li><li>Jothi, R., Cuddapah, S., Barski, A., Cui, K., Zhao, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Genome-wide+identification+of+in+vivo+protein-DNA+binding+sites+from+ChIP-Seq+data.">Genome-wide identification of in vivo protein-DNA binding sites from ChIP-Seq data.</a> Nucleic Acids Res. 36, 5221-5231 (2008).</li><li>Qin, Z. S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=HPeak:+an+HMM-based+algorithm+for+defining+read-enriched+regions+in+ChIP-Seq+data.">HPeak: an HMM-based algorithm for defining read-enriched regions in ChIP-Seq data.</a> BMC Bioinformatics. 11, 369 (2010).</li><li>Song, Q., Smith, A. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Identifying+dispersed+epigenomic+domains+from+ChIP-Seq+data.">Identifying dispersed epigenomic domains from ChIP-Seq data.</a> Bioinformatics. 27, 870-871 (2011).</li><li>Spyrou, C., Stark, R., Lynch, A. G., Tavar&#233;, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=BayesPeak:+Bayesian+analysis+of+ChIP-seq+data.">BayesPeak: Bayesian analysis of ChIP-seq data.</a> BMC Bioinformatics. 10, 299 (2009).</li><li>Lai, T., Xing, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+simple+Bayesian+approach+to+multiple+change-points.">A simple Bayesian approach to multiple change-points.</a> Statistica Sinica. , (2011).</li><li>Robertson, G., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Genome-wide+profiles+of+STAT1+DNA+association+using+chromatin+immunoprecipitation+and+massively+parallel+sequencing.">Genome-wide profiles of STAT1 DNA association using chromatin immunoprecipitation and massively parallel sequencing.</a> Nat. Methods. 4, 651-657 (2007).</li><li>Stitzel, M. L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Global+epigenomic+analysis+of+primary+human+pancreatic+islets+provides+insights+into+type+2+diabetes+susceptibility+loci.">Global epigenomic analysis of primary human pancreatic islets provides insights into type 2 diabetes susceptibility loci.</a> Cell Metab. 12, 443-455 (2010).</li><li>Bernstein, B. E., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+NIH+Roadmap+Epigenomics+Mapping+Consortium.">The NIH Roadmap Epigenomics Mapping Consortium.</a> Nat. Biotechnol. 28, 1045-1048 (2010).</li><li>Karolchik, D., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+UCSC+Table+Browser+data+retrieval+tool.">The UCSC Table Browser data retrieval tool.</a> Nucleic Acids Res. 32, 493-496 (2004).</li><li>Matys, V., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=TRANSFAC:+transcriptional+regulation,+from+patterns+to+profiles.">TRANSFAC: transcriptional regulation, from patterns to profiles.</a> Nucleic Acids Res. 31, 374-378 (2003).</li><li>Portales-Casamar, E., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=JASPAR+2010:+the+greatly+expanded+open-access+database+of+transcription+factor+binding+profiles.">JASPAR 2010: the greatly expanded open-access database of transcription factor binding profiles.</a> Nucleic Acids Res. 38, D105-D110 (2010).</li></ol>

الإعلان عن أي تضارب في المصالح.

شرعنا في تطوير نموذج لتحليل البيانات التي يمكن أن ChIPseq تحديد كل منقط ومنتشر بشكل جيد على قدم المساواة هياكل البيانات. حتى الآن، كانت مناطق التخصيب، ولا سيما المناطق المنتشر، والتي تعكس حجم التوقع يفترض من جزيرة كبيرة ويصعب التعرف عليها. لمعالجة هذه المشاكل، ونحن است?...

<table border="1" style=";text-align:right;direction:rtl"><tbody><tr><td> اسم كاشف </td><td> شركة </td><td> كتالوج رقم </td><td> التعليقات (اختياري) </td></tr><tr><td> لينكس على أساس محطة العمل </td><td></td><td></td><td></td></tr></tbody></table>

a novel bayesian change-point algorithm for genome-wide analysis of diverse chipseq data types

ChIPseq هو أسلوب يستخدم على نطاق واسع للتحقيق في البروتين DNA التفاعلات. يتم إنشاء ملفات تعريف الكثافة قراءة باستخدام التسلسل التالي من البروتين DNA محددة وقصيرة محاذاة يقرأ إلى الجينوم مرجعية. وكشف مناطق التخصيب والقمم، والتي تختلف في كثير من الأحيان بشكل كبير في الشكل، اعتمادا على البروتين الهدف 1. على سبيل المثال، غالبا ما تربط عوامل النسخ في موقع وبطريقة تسلسل معين وتميل إلى إنتاج الذروة نقطي، بينما هي تعديلات بسيطة أكثر انتشارا وتتميز الجزر، واسعة الانتشار من تخصيب 2. تحديد هذه المناطق بشكل موثوق كان محور عملنا. استخدمت خوارزميات لتحليل البيانات ChIPseq منهجيات مختلفة، من الاستدلال 3-5 على نماذج أكثر صرامة الإحصائية، على سبيل المثال نماذج ماركوف المخفية (HMMs) 6-8. سعينا إلى حل تقلل من ضرورة يصعب تحديد والمخصصة المعلمات التي غالبا ماتنازلات القرار ويقلل من قابليتها للاستخدام بديهية من الأداة. فيما يتعلق HMM القائم على الأساليب، ونحن تهدف للحد من إجراءات تقدير المعلمة وبسيطة، والتصنيفات الدولة محدودة التي تستخدم في كثير من الأحيان. بالإضافة إلى ذلك، تحليل البيانات التقليدية ChIPseq ينطوي التصنيف من المتوقع قراءة ملامح كثافة نقطية أو إما منتشر ثم طلب بعد ذلك الأداة المناسبة. نحن تهدف إلى زيادة الحاجة إلى استبدال هذين النموذجين متميزة مع نموذج واحد أكثر تنوعا، والتي يمكن أن تعالج باقتدار طائفة كاملة من أنواع البيانات. لتحقيق هذه الأهداف، ونحن لأول مرة بناء إطار إحصائي أن غرار طبيعي ChIPseq هياكل البيانات باستخدام مسبقا في طليعة HMMs 9، والتي تستخدم فقط الصيغ الصريحة، والابتكار حاسما لمزايا أدائها. نماذج الكشف عن مجريات الأمور أكثر تعقيدا بعد ذلك، لدينا تسع دول HMM مخفي لا حصر له من خلالالنظرية الافتراضية النموذج. طبقنا لتحديد نقاط تغيير معقول في كثافة القراءة، التي تحدد مزيد من شرائح تخصيب اليورانيوم. كشف تحليلنا كيف لنا نقطة تغيير النظرية الافتراضية (BCP) خوارزمية كان التعقيد يشهد انخفاض الحسابية من قبل وقت التشغيل مختصرة وأثر الذاكرة. تم تطبيق الخوارزمية بنجاح BCP إلى كل من الذروة ونقطي منتشر تحديد الجزيرة مع دقة قوية ومحدودة المعلمات المعرفة من قبل المستخدم. هذا يتضح كلا من براعة وسهولة الاستخدام. وبناء على ذلك، فإننا نعتقد أنه يمكن تنفيذها بسهولة في مدى واسع من أنواع البيانات والمستخدمين النهائيين على نحو تتم مقارنة بسهولة ويتناقض، مما يجعلها أداة عظيمة لتحليل البيانات ChIPseq التي يمكن أن تساعد في التعاون وتأييد بين المجموعات البحثية. هنا، علينا أن نبرهن تطبيق BCP إلى عامل النسخ الموجودة والبيانات 10،11 اللاجينية 12 إلى توضيح فائدتها.

BCP تتفوق في تحديد مناطق واسعة في تخصيب تعديل البيانات هيستون. كنقطة مرجعية، ونحن في السابق مقارنة نتائجنا لتلك التي SICER 3، أداة القائمة التي أثبتت أداء قويا. لتوضيح مزايا أفضل BCP، ودرسنا على تعديل هيستون التي تم دراستها بشكل جيد لإرساء أساس لتقييم معدلات النجاح. ?...

Watch this Scientific Journal Video about A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types at JoVE.com

A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types

تغيير وجهة نظرنا النظرية الافتراضية (BCP) خوارزمية يستند دولة من بين الفن النمذجة التقدم في التغيير عبر نقاط نماذج ماركوف المخفية ويطبقها على لونين مناعي التسلسل (ChIPseq) تحليل البيانات. BCP يؤدي جيدا في كل أنواع البيانات واسعة النطاق والمنقط، ولكن تتفوق في تحديد بدقة قوية والجزر استنساخه من تخصيب هيستون منتشر.

رواية النظرية الافتراضية تغيير نقطة حسابي لتحليل الجينوم-اسعة من أنواع البيانات المتنوعة ChIPseq

ChIPseq is a widely used technique for investigating protein-DNA interactions. Read density profiles are generated by using next-sequencing of ...

a-novel-bayesian-change-point-algorithm-for-genome-wide-analysis

Research

JoVE Journal

Biology

11.2K Views.  Stony Brook University. تغيير وجهة نظرنا النظرية الافتراضية (BCP) خوارزمية يستند دولة من بين الفن النمذجة التقدم في التغيير عبر نقاط نماذج ماركوف المخفية ويطبقها على لونين مناعي التسلسل (ChIPseq) تحليل البيانات. BCP يؤدي جيدا في كل أنواع البيانات واسعة النطاق والمنقط، ولكن تتفوق في تحديد بدق?...

Video: A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types

A Neuronal and Astrocyte Co-Culture Assay for High Content Analysis of Neurotoxicity

High Content Analysis (HCA) assays combine cells and detection reagents with automated imaging and powerful image analysis algorithms, allowing measurement of multiple cellular phenotypes within a single assay. In this study, we utilized HCA to develop a novel assay for neurotoxicity. Neurotoxicity assessment represents an important part of drug safety evaluation, as well as being a significant focus of environmental protection efforts. Additionally, neurotoxicity is also a well-accepted in vitro marker of the development of neurodegenerative diseases such as Alzheimer's and Parkinson's diseases. Recently, the application of HCA to neuronal screening has been reported. By labeling neuronal cells with &beta;III-tubulin, HCA assays can provide high-throughput, non-subjective, quantitative measurements of parameters such as neuronal number, neurite count and neurite length, all of which can indicate neurotoxic effects. However, the role of astrocytes remains unexplored in these models. Astrocytes have an integral role in the maintenance of central nervous system (CNS) homeostasis, and are associated with both neuroprotection and neurodegradation when they are activated in response to toxic substances or disease states. GFAP is an intermediate filament protein expressed predominantly in the astrocytes of the CNS. Astrocytic activation (gliosis) leads to the upregulation of GFAP, commonly accompanied by astrocyte proliferation and hypertrophy. This process of reactive gliosis has been proposed as an early marker of damage to the nervous system. The traditional method for GFAP quantitation is by immunoassay. This approach is limited by an inability to provide information on cellular localization, morphology and cell number. We determined that HCA could be used to overcome these limitations and to simultaneously measure multiple features associated with gliosis - changes in GFAP expression, astrocyte hypertrophy, and astrocyte proliferation - within a single assay. In co-culture studies, astrocytes have been shown to protect neurons against several types of toxic insult and to critically influence neuronal survival. Recent studies have suggested that the use of astrocytes in an in vitro neurotoxicity test system may prove more relevant to human CNS structure and function than neuronal cells alone. Accordingly, we have developed an HCA assay for co-culture of neurons and astrocytes, comprised of protocols and validated, target-specific detection reagents for profiling &beta;III-tubulin and glial fibrillary acidic protein (GFAP). This assay enables simultaneous analysis of neurotoxicity, neurite outgrowth, gliosis, neuronal and astrocytic morphology and neuronal and astrocytic development in a wide variety of cellular models, representing a novel, non-subjective, high-throughput assay for neurotoxicity assessment. The assay holds great potential for enhanced detection of neurotoxicity and improved productivity in neuroscience research and drug discovery.

This article describes a novel protocol and reagent set designed for sensitive measurement of neurotoxic effects of compounds and treatments on co-cultures of neurons and astrocytes using high content analysis. Results demonstrate that high content analysis represents an exciting novel technology for neurotoxicity assessment.

والخلايا العصبية ونجمية المشارك الثقافة الفحص لتحليل محتوى عال من العصبية

High Content Analysis (HCA) assays combine cells and detection reagents with automated imaging and powerful image analysis algorithms, allowing ...

Genome-wide Analysis of Aminoacylation (Charging) Levels of tRNA Using Microarrays

tRNA aminoacylation, or charging, levels can rapidly change within a cell in response to the environment[1]. Changes in tRNA charging levels in both prokaryotic and eukaryotic cells lead to translational regulation which is a major cellular mechanism of stress response. Familiar examples are the stringent response in E. coli and the Gcn2 stress response pathway in yeast ([2-6]). Recent work in E. coli and S. cerevisiae have shown that tRNA charging patterns are highly dynamic and depends on the type of stress experienced by cells [1, 6, 7]. The highly dynamic, variable nature of tRNA charging makes it essential to determine changes in tRNA charging levels at the genomic scale, in order to fully elucidate cellular response to environmental variations. In this review we present a method for simultaneously measuring the relative charging levels of all tRNAs in S. cerevisiae . While the protocol presented here is for yeast, this protocol has been successfully applied for determining relative charging levels in a wide variety of organisms including E. coli and human cell cultures[7, 8].

Genome-wide Analysis of Aminoacylation Charging Levels of tRNA Using Microarrays

We describe a method for microarray analysis to determine relative aminoacylation levels of all tRNAs from S. cerivisiae.

الجينوم على نطاق تحليل المستويات (شحن) من الحمض الريبي النووي النقال باستخدام Aminoacylation ميكروأرس]

tRNA aminoacylation, or charging, levels can rapidly change within a cell in response to the environment[1]. Changes in tRNA charging levels in both ...

Genome-wide Analysis using ChIP to Identify Isoform-specific Gene Targets

Recruitment of transcriptional and epigenetic factors to their targets is a key step in their regulation. Prominently featured in recruitment are the protein domains that bind to specific histone modifications. One such domain is the plant homeodomain (PHD), found in several chromatin-binding proteins. The epigenetic factor RBP2 has multiple PHD domains, however, they have different functions (Figure 4). In particular, the C-terminal PHD domain, found in a RBP2 oncogenic fusion in human leukemia, binds to trimethylated lysine 4 in histone H3 (H3K4me3)1. The transcript corresponding to the RBP2 isoform containing the C-terminal PHD accumulates during differentiation of promonocytic, lymphoma-derived, U937 cells into monocytes2. Consistent with both sets of data, genome-wide analysis showed that in differentiated U937 cells, the RBP2 protein gets localized to genomic regions highly enriched for H3K4me33. Localization of RBP2 to its targets correlates with a decrease in H3K4me3 due to RBP2 histone demethylase activity and a decrease in transcriptional activity. In contrast, two other PHDs of RBP2 are unable to bind H3K4me3. Notably, the C-terminal domain PHD of RBP2 is absent in the smaller RBP2 isoform4. It is conceivable that the small isoform of RBP2, which lacks interaction with H3K4me3, differs from the larger isoform in genomic location. The difference in genomic location of RBP2 isoforms may account for the observed diversity in RBP2 function. Specifically, RBP2 is a critical player in cellular differentiation mediated by the retinoblastoma protein (pRB). Consistent with these data, previous genome-wide analysis, without distinction between isoforms, identified two distinct groups of RBP2 target genes: 1) genes bound by RBP2 in a manner that is independent of differentiation; 2) genes bound by RBP2 in a differentiation-dependent manner.
To identify differences in localization between the isoforms we performed genome-wide location analysis by ChIP-Seq. Using antibodies that detect both RBP2 isoforms we have located all RBP2 targets. Additionally we have antibodies that only bind large, and not small RBP2 isoform (Figure 4). After identifying the large isoform targets, one can then subtract them from all RBP2 targets to reveal the targets of small isoform. These data show the contribution of chromatin-interacting domain in protein recruitment to its binding sites in the genome.

Here we are presenting a chromatin immunoprecipitation (ChIP) procedure for genome-wide location analysis of protein isoforms that differ in a histone-binding domain. We are applying it to ChIP-Seq analysis to identify the targets of the KDM5A/JARID1A/RBP2 histone demethylase.

الجينوم على نطاق التحليل باستخدام رقاقة لتحديد أهداف محددة الجينات شكل الإسوي

Recruitment of transcriptional and epigenetic factors to their targets is a key step in their regulation. Prominently featured in recruitment are the ...

Genome-wide Screen for miRNA Targets Using the MISSION Target ID Library

The Target ID Library is designed to assist in discovery and identification of microRNA (miRNA) targets. The Target ID Library is a plasmid-based, genome-wide cDNA library cloned into the 3'UTR downstream from the dual-selection fusion protein, thymidine kinase-zeocin (TKzeo). The first round of selection is for stable transformants, followed with introduction of a miRNA of interest, and finally, selecting for cDNAs containing the miRNA's target. Selected cDNAs are identified by sequencing (see Figure 1-3 for Target ID Library Workflow and details).
To ensure broad coverage of the human transcriptome, Target ID Library cDNAs were generated via oligo-dT priming using a pool of total RNA prepared from multiple human tissues and cell lines. Resulting cDNA range from 0.5 to 4 kb, with an average size of 1.2 kb, and were cloned into the p3&#900;TKzeo dual-selection plasmid (see Figure 4 for plasmid map). The gene targets represented in the library can be found on the Sigma-Aldrich webpage. Results from Illumina sequencing (Table 3), show that the library includes 16,922 of the 21,518 unique genes in UCSC RefGene (79%), or 14,000 genes with 10 or more reads (66%).

The Target ID Library is a plasmid-based, genome-wide collection of cloned cDNA used to identify miRNA targets. Here we demonstrate its use and application.

الجينوم على نطاق الشاشة لأهداف ميرنا باستخدام معرف الهدف المكتبة MISSION

The Target ID Library is designed to assist in discovery and identification of microRNA (miRNA) targets. The Target ID Library is a plasmid-based, ...

Quantitative and Automated High-throughput Genome-wide RNAi Screens in C. elegans

RNA interference is a powerful method to understand gene function, especially when conducted at a whole-genome scale and in a quantitative context. In C. elegans, gene function can be knocked down simply and efficiently by feeding worms with bacteria expressing a dsRNA corresponding to a specific gene 1. While the creation of libraries of RNAi clones covering most of the C. elegans genome 2,3 opened the way for true functional genomic studies (see for example 4-7), most established methods are laborious. Moy and colleagues have developed semi-automated protocols that facilitate genome-wide screens 8. The approach relies on microscopic imaging and image analysis. 
	Here we describe an alternative protocol for a high-throughput genome-wide screen, based on robotic handling of bacterial RNAi clones, quantitative analysis using the COPAS Biosort (Union Biometrica (UBI)), and an integrated software: the MBioLIMS (Laboratory Information Management System from Modul-Bio) a technology that provides increased throughput for data management and sample tracking. The method allows screens to be conducted on solid medium plates. This is particularly important for some studies, such as those addressing host-pathogen interactions in C. elegans, since certain microbes do not efficiently infect worms in liquid culture.
	We show how the method can be used to quantify the importance of genes in anti-fungal innate immunity in C. elegans. In this case, the approach relies on the use of a transgenic strain carrying an epidermal infection-inducible fluorescent reporter gene, with GFP under the control of the promoter of the antimicrobial peptide gene nlp 29 and a red fluorescent reporter that is expressed constitutively in the epidermis. The latter provides an internal control for the functional integrity of the epidermis and nonspecific transgene silencing9. When control worms are infected by the fungus they fluoresce green. Knocking down by RNAi a gene required for nlp 29 expression results in diminished fluorescence after infection. Currently, this protocol allows more than 3,000 RNAi clones to be tested and analyzed per week, opening the possibility of screening the entire genome in less than 2 months.

Quantitative and Automated High-throughput Genome-wide RNAi Screens in C. elegans

We describe a protocol using C. elegans and RNAi feeding libraries that allows automated measurement of multiple parameters such as fluorescence, size and opacity of individual worms in a population. We give one example of a screen to identify genes involved in anti-fungal innate immunity in C. elegans.

الكمية والآلي عالية الإنتاجية الجينوم على نطاق شاشات رني في C. ايليجانس</em

RNA interference is a powerful method to understand gene function, especially when conducted at a whole-genome scale and in a quantitative context. In C. ...

Genome-wide Gene Deletions in Streptococcus sanguinis by High Throughput PCR

Transposon mutagenesis and single-gene deletion are two methods applied in genome-wide gene knockout in bacteria 1,2. Although transposon mutagenesis is less time consuming, less costly, and does not require completed genome information, there are two weaknesses in this method: (1) the possibility of a disparate mutants in the mixed mutant library that counter-selects mutants with decreased competition; and (2) the possibility of partial gene inactivation whereby genes do not entirely lose their function following the insertion of a transposon. Single-gene deletion analysis may compensate for the drawbacks associated with transposon mutagenesis. To improve the efficiency of genome-wide single gene deletion, we attempt to establish a high-throughput technique for genome-wide single gene deletion using Streptococcus sanguinis as a model organism. Each gene deletion construct in S. sanguinis genome is designed to comprise 1-kb upstream of the targeted gene, the aphA-3 gene, encoding kanamycin resistance protein, and 1-kb downstream of the targeted gene. Three sets of primers F1/R1, F2/R2, and F3/R3, respectively, are designed and synthesized in a 96-well plate format for PCR-amplifications of those three components of each deletion construct. Primers R1 and F3 contain 25-bp sequences that are complementary to regions of the aphA-3 gene at their 5' end. A large scale PCR amplification of the aphA-3 gene is performed once for creating all single-gene deletion constructs. The promoter of aphA-3 gene is initially excluded to minimize the potential polar effect of kanamycin cassette. To create the gene deletion constructs, high-throughput PCR amplification and purification are performed in a 96-well plate format. A linear recombinant PCR amplicon for each gene deletion will be made up through four PCR reactions using high-fidelity DNA polymerase. The initial exponential growth phase of S. sanguinis cultured in Todd Hewitt broth supplemented with 2.5% inactivated horse serum is used to increase competence for the transformation of PCR-recombinant constructs. Under this condition, up to 20% of S. sanguinis cells can be transformed using ~50 ng of DNA. Based on this approach, 2,048 mutants with single-gene deletion were ultimately obtained from the 2,270 genes in S. sanguinis excluding four gene ORFs contained entirely within other ORFs in S. sanguinis SK36 and 218 potential essential genes. The technique on creating gene deletion constructs is high throughput and could be easy to use in genome-wide single gene deletions for any transformable bacteria.

Genome-wide Gene Deletions in Streptococcus sanguinis by High Throughput PCR

An efficient genome-wide single gene mutation method has been established using Streptococcus sanguinis as a model organism. This method has achieved via high throughput recombinant PCRs and transformations.

حذوفات الجينات في الجينوم على نطاق<em&gt; العقدية الدم</em&gt; من جانب PCR إنتاجية عالية

Transposon  mutagenesis and single-gene deletion are two methods applied in genome-wide  gene knockout in bacteria 1,2. Although transposon mutagenesis is ...

Polysome Fractionation and Analysis of Mammalian Translatomes on a Genome-wide Scale

mRNA translation plays a central role in the regulation of gene expression and represents the most energy consuming process in mammalian cells. Accordingly, dysregulation of mRNA translation is considered to play a major role in a variety of pathological states including cancer. Ribosomes also host chaperones, which facilitate folding of nascent polypeptides, thereby modulating function and stability of newly synthesized polypeptides. In addition, emerging data indicate that ribosomes serve as a platform for a repertoire of signaling molecules, which are implicated in a variety of post-translational modifications of newly synthesized polypeptides as they emerge from the ribosome, and/or components of translational machinery. Herein, a well-established method of ribosome fractionation using sucrose density gradient centrifugation is described. In conjunction with the in-house developed &#8220;anota&#8221; algorithm this method allows direct determination of differential translation of individual mRNAs on a genome-wide scale. Moreover, this versatile protocol can be used for a variety of biochemical studies aiming to dissect the function of ribosome-associated protein complexes, including those that play a central role in folding and degradation of newly synthesized polypeptides.

Ribosomes play a central role in protein synthesis. Polyribosome (polysome) fractionation by sucrose density gradient centrifugation allows direct determination of translation efficiencies of individual mRNAs on a genome-wide scale. In addition, this method can be used for biochemical analysis of ribosome- and polysome-associated factors such as chaperones and signaling molecules.

Polysome تجزئة وتحليل الثدييات Translatomes على مقياس الجينوم على نطاق

mRNA translation plays a central role in the regulation of gene expression and represents the most energy consuming process in mammalian cells. ...

Genome-wide Mapping of Drug-DNA Interactions in Cells with COSMIC (Crosslinking of Small Molecules to Isolate Chromatin)

The genome is the target of some of the most effective chemotherapeutics, but most of these drugs lack DNA sequence specificity, which leads to dose-limiting toxicity and many adverse side effects. Targeting the genome with sequence-specific small molecules may enable molecules with increased therapeutic index and fewer off-target effects. N-methylpyrrole/N-methylimidazole polyamides are molecules that can be rationally designed to target specific DNA sequences with exquisite precision. And unlike most natural transcription factors, polyamides can bind to methylated and chromatinized DNA without a loss in affinity. The sequence specificity of polyamides has been extensively studied in vitro with cognate site identification (CSI) and with traditional biochemical and biophysical approaches, but the study of polyamide binding to genomic targets in cells remains elusive. Here we report a method, the crosslinking of small molecules to isolate chromatin (COSMIC), that identifies polyamide binding sites across the genome. COSMIC is similar to chromatin immunoprecipitation (ChIP), but differs in two important ways: (1) a photocrosslinker is employed to enable selective, temporally-controlled capture of polyamide binding events, and (2) the biotin affinity handle is used to purify polyamide&#8211;DNA conjugates under semi-denaturing conditions to decrease DNA that is non-covalently bound. COSMIC is a general strategy that can be used to reveal the genome-wide binding events of polyamides and other genome-targeting chemotherapeutic agents.

Genome-wide Mapping of Drug-DNA Interactions in Cells with COSMIC Crosslinking of Small Molecules to Isolate Chromatin

Identifying the direct targets of genome-targeting molecules remains a major challenge. To understand how DNA-binding molecules engage the genome, we developed a method that relies on crosslinking of small molecules to isolate chromatin (COSMIC).

على صعيد رسم الخرائط الجينوم من المخدرات-DNA التفاعلات في الخلايا مع COSMIC (يشابك من الجزيئات الصغيرة لعزل لونين)

The genome is the target of some of the most effective chemotherapeutics, but most of these drugs lack DNA sequence specificity, which leads to ...

Genome-wide Purification of Extrachromosomal Circular DNA from Eukaryotic Cells

Extrachromosomal circular DNAs (eccDNAs) are common genetic elements in Saccharomyces cerevisiae and are reported in other eukaryotes as well. EccDNAs contribute to genetic variation among somatic cells in multicellular organisms and to evolution of unicellular eukaryotes. Sensitive methods for detecting eccDNA are needed to clarify how these elements affect genome stability and how environmental and biological factors&#160;induce their formation in eukaryotic cells. This video presents a sensitive eccDNA-purification method called Circle-Seq. The method encompasses column purification of circular DNA, removal of remaining linear chromosomal DNA, rolling-circle amplification of eccDNA, deep sequencing, and mapping. Extensive exonuclease treatment&#160;was&#160;required for sufficient linear chromosomal DNA degradation. The rolling-circle amplification step by &#966;29 polymerase enriched for circular DNA over linear DNA. Validation of the Circle-Seq method on three S. cerevisiae CEN.PK populations of 1010 cells detected hundreds of eccDNA profiles in sizes larger than 1 kilobase. Repeated findings of ASP3-1, COS111, CUP1, RSC30,&#160;HXT6, HXT7 genes on circular DNA in both S288c and CEN.PK suggests that DNA circularization is conserved between strains at these loci. In sum, the Circle-Seq method has broad applicability for genome-scale screening for eccDNA in eukaryotes as well as for detecting specific eccDNA types.

This paper presents a sensitive method called Circle-Seq for purifying extrachromosomal circular DNA (eccDNA). The method encompasses column purification, removal of remaining linear chromosomal DNA, rolling-circle amplification and high-throughput sequencing. Circle-Seq is applicable to genome-scale screening of eukaryotic eccDNA and studying genome instability and copy-number variation.

تنقية الجينوم على نطاق خارج الصبغي التعميم الحمض النووي من خلايا حقيقية النواة

Extrachromosomal circular DNAs (eccDNAs) are common genetic elements in Saccharomyces cerevisiae and are reported in other eukaryotes as well. EccDNAs ...

Comprehensive Workflow for the Genome-wide Identification and Expression Meta-analysis of the ATL E3 Ubiquitin Ligase Gene Family in Grapevine

Classification and nomenclature of genes in a family can significantly contribute to the description of the diversity of encoded proteins and to the prediction of family functions based on several features, such as the presence of sequence motifs or of particular sites for post-translational modification and the expression profile of family members in different conditions. This work describes a detailed protocol for gene family characterization. Here, the procedure is applied to the characterization of the Arabidopsis T&#243;xicos in Levadura (ATL) E3 ubiquitin ligase family in grapevine. The methods include the genome-wide identification of family members, the characterization of gene localization, structure, and duplication, the analysis of conserved protein motifs, the prediction of protein localization and phosphorylation sites as well as gene expression profiling across the family in different datasets. Such procedure, which could be extended to further analyses depending on experimental purposes, could be applied to any gene family in any plant species for which genomic data are available, and it provides valuable information to identify interesting candidates for functional studies, giving insights into the molecular mechanisms of plant adaptation to their environment.

This article describes the procedure for the identification and characterization of a gene family in grapevine applied to the family of Arabidopsis T&#243;xicos in Levadura (ATL) E3 ubiquitin ligases.

سير عمل شامل للتعرف على نطاق الجينوم والتحليل التلوي التعبير الأسرة الجينات ATL E3 Ubiquitin ليجاسى في الكرمة

Classification and nomenclature of genes in a family can significantly contribute to the description of the diversity of encoded proteins and to the ...