28 research outputs found

    Necessary and Sufficient Conditions for Inverse Reinforcement Learning of Bayesian Stopping Time Problems

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    This paper presents an inverse reinforcement learning~(IRL) framework for Bayesian stopping time problems. By observing the actions of a Bayesian decision maker, we provide a necessary and sufficient condition to identify if these actions are consistent with optimizing a cost function. In a Bayesian (partially observed) setting, the inverse learner can at best identify optimality wrt the observed actions. Our IRL algorithm identifies optimality and then constructs set valued estimates of the cost function. To achieve this IRL objective, we use novel ideas from Bayesian revealed preferences stemming from microeconomics. We illustrate the proposed IRL scheme using two important examples of stopping time problems, namely, sequential hypothesis testing and Bayesian search. Finally, for finite datasets, we propose an IRL detection algorithm and give finite sample bounds on its error probabilities

    Gene Discovery and Advances in Finger Millet [Eleusine coracana (L.) Gaertn.] Genomics—An Important Nutri-Cereal of Future

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    The rapid strides in molecular marker technologies followed by genomics, and next generation sequencing advancements in three major crops (rice, maize and wheat) of the world have given opportunities for their use in the orphan, but highly valuable future crops, including finger millet [Eleusine coracana (L.) Gaertn.]. Finger millet has many special agronomic and nutritional characteristics, which make it an indispensable crop in arid, semi-arid, hilly and tribal areas of India and Africa. The crop has proven its adaptability in harsh conditions and has shown resilience to climate change. The adaptability traits of finger millet have shown the advantage over major cereal grains under stress conditions, revealing it as a storehouse of important genomic resources for crop improvement. Although new technologies for genomic studies are now available, progress in identifying and tapping these important alleles or genes is lacking. RAPDs were the default choice for genetic diversity studies in the crop until the last decade, but the subsequent development of SSRs and comparative genomics paved the way for the marker assisted selection in finger millet. Resistance gene homologues from NBS-LRR region of finger millet for blast and sequence variants for nutritional traits from other cereals have been developed and used invariably. Population structure analysis studies exhibit 2-4 sub-populations in the finger millet gene pool with separate grouping of Indian and exotic genotypes. Recently, the omics technologies have been efficiently applied to understand the nutritional variation, drought tolerance and gene mining. Progress has also occurred with respect to transgenics development. This review presents the current biotechnological advancements along with research gaps and future perspective of genomic research in finger millet

    Identification of antisense nucleic acid hybridization sites in mRNA molecules with self-quenching fluorescent reporter molecules

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    We describe a physical mRNA mapping strategy employing fluorescent self-quenching reporter molecules (SQRMs) that facilitates the identification of mRNA sequence accessible for hybridization with antisense nucleic acids in vitro and in vivo, real time. SQRMs are 20–30 base oligodeoxynucleotides with 5–6 bp complementary ends to which a 5′ fluorophore and 3′ quenching group are attached. Alone, the SQRM complementary ends form a stem that holds the fluorophore and quencher in contact. When the SQRM forms base pairs with its target, the structure separates the fluorophore from the quencher. This event can be reported by fluorescence emission when the fluorophore is excited. The stem–loop of the SQRM suggests that SQRM be made to target natural stem–loop structures formed during mRNA synthesis. The general utility of this method is demonstrated by SQRM identification of targetable sequence within c-myb and bcl-6 mRNA. Corresponding antisense oligonucleotides reduce these gene products in cells

    Altering, Improving, And Defining The Specificities Of Crispr-Cas Nucleases

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    CRISPR-Cas9 nucleases have been widely adopted for genome editing applications to knockout genes or to introduce desired changes. While these nucleases have shown immense promise, two notable limitations of the wild-type form of the broadly used Streptococcus pyogenes Cas9 (SpCas9) are the restriction of targeting range to sites that contain an NGG protospacer adjacent motif (PAM), and the undesirable ability of the enzyme to cleave off-target sites that resemble the on-target site. Scarcity of PAM motifs can limit implementations that require precise targeting, whereas off-target effects can confound research applications and are important considerations for therapeutics. To improve the targeting range of SpCas9 and an orthogonal Cas9 from Staphylococcus aureus (called SaCas9), we optimized a heterologous genetic selection system that enabled us to perform directed evolution of PAM specificity. With SpCas9, we evolved two separate variants that can target NGA and NGCG PAMs1, and with SaCas9 relaxed the PAM from NNGRRT to NNNRRT2, increasing the targetability of these enzyme 2- to 4-fold. The genome-wide specificity profiles of SpCas9 and SaCas9 variants, determine by GUIDE-seq3, indicate that they are at least as, if not more, specific than the wild-type enzyme1,2. Together, these results demonstrate that the inherent PAM specificity of multiple different Cas9 orthologues can be purposefully modified to improve the accuracy of targeting. Existing strategies for improving the genome-wide specificity of SpCas9 have thus far proven to be incompletely effective and/or have other limitations that constrain their use. To address the off-target potential of SpCas9, we engineered a high-fidelity variant of SpCas9 (called SpCas9-HF1), that contains alterations designed to reduce non-specific contacts to the target strand DNA backbone. In comparison to wild-type SpCas9, SpCas9-HF1 rendered all or nearly all off-target events imperceptible by GUIDE-seq and targeted deep-sequencing methods with standard non-repetitive target sites in human cells4. Even for atypical, repetitive target sites, the vast majority of off-targets induced by SpCas9-HF1 and optimized derivatives were not detected4. With its exceptional precision, SpCas9-HF1 provides an important and easily employed alternative to wild-type SpCas9 that can eliminate off-target effects when using CRISPR-Cas9 for research and therapeutic applications. Finally, on-target activity and genome-wide specificity are two important properties of engineered nucleases that should be characterized prior to adoption of such technologies for research or therapeutic applications. CRISPR-Cas Cpf1 nucleases have recently been described as an alternative genome-editing platform5, yet their activities and genome-wide specificities remain largely undefined. Based on assessment of on-target activity across more than 40 target sites, we demonstrate that two Cpf1 orthologues function robustly in human cells with efficiencies comparable to those of the widely used Streptococcus pyogenes Cas9. We also demonstrate that four to six bases at the 3’ end of the short CRISPR RNA (crRNA) used to program Cpf1 are insensitive to single base mismatches, but that many of the other bases within the crRNA targeting region are highly sensitive to single or double substitutions6. Consistent with these results, GUIDE-seq performed in multiple cell types and targeted deep sequencing analyses of two Cpf1 nucleases revealed no detectable off-target cleavage for over half of 20 different crRNAs we examined. Our results suggest that the two Cpf1 nucleases we characterized generally possess robust on-target activity and high specificities in human cells, findings that should encourage broader use of these genome editing enzymes. 1. Kleinstiver, BP, et al. (2015) Nature, 523(7561):481-5 2. Kleinstiver, BP, et al. (2015) Nature Biotechnology, 33(12):1293-98 3. Tsai, SQ et al. (2015) Nature Biotechnology, 33(2):187-97 4. Kleinstiver, BP and Pattanayak, V, et al. (2016), Nature, 529(7587):490-5 5. Zetsche, B, et al. (2015) Cell, 163(3):759-71 6. Kleinstiver, BP and Tsai, SQ, et al. (2016), Nature Biotechnology, 34(8):869-7
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