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      Paralog editing tunes rice stomatal density to maintain photosynthesis and improve drought tolerance

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          Abstract

          Rice (Oryza sativa) is of paramount importance for global nutrition, supplying at least 20% of global calories. However, water scarcity and increased drought severity are anticipated to reduce rice yields globally. We explored stomatal developmental genetics as a mechanism for improving drought resilience in rice while maintaining yield under climate stress. CRISPR/Cas9-mediated knockouts of the positive regulator of stomatal development STOMAGEN and its paralog EPIDERMAL PATTERNING FACTOR-LIKE10 (EPFL10) yielded lines with ∼25% and 80% of wild-type stomatal density, respectively. epfl10 lines with moderate reductions in stomatal density were able to conserve water to similar extents as stomagen lines but did not suffer from the concomitant reductions in stomatal conductance, carbon assimilation, or thermoregulation observed in stomagen knockouts. Moderate reductions in stomatal density achieved by editing EPFL10 present a climate-adaptive approach for safeguarding yield in rice. Editing the paralog of STOMAGEN in other species may provide a means for tuning stomatal density in agriculturally important crops beyond rice.

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          Is Open Access

          MAFFT Multiple Sequence Alignment Software Version 7: Improvements in Performance and Usability

          We report a major update of the MAFFT multiple sequence alignment program. This version has several new features, including options for adding unaligned sequences into an existing alignment, adjustment of direction in nucleotide alignment, constrained alignment and parallel processing, which were implemented after the previous major update. This report shows actual examples to explain how these features work, alone and in combination. Some examples incorrectly aligned by MAFFT are also shown to clarify its limitations. We discuss how to avoid misalignments, and our ongoing efforts to overcome such limitations.
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            MUSCLE: multiple sequence alignment with high accuracy and high throughput.

            We describe MUSCLE, a new computer program for creating multiple alignments of protein sequences. Elements of the algorithm include fast distance estimation using kmer counting, progressive alignment using a new profile function we call the log-expectation score, and refinement using tree-dependent restricted partitioning. The speed and accuracy of MUSCLE are compared with T-Coffee, MAFFT and CLUSTALW on four test sets of reference alignments: BAliBASE, SABmark, SMART and a new benchmark, PREFAB. MUSCLE achieves the highest, or joint highest, rank in accuracy on each of these sets. Without refinement, MUSCLE achieves average accuracy statistically indistinguishable from T-Coffee and MAFFT, and is the fastest of the tested methods for large numbers of sequences, aligning 5000 sequences of average length 350 in 7 min on a current desktop computer. The MUSCLE program, source code and PREFAB test data are freely available at http://www.drive5. com/muscle.
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              BUSCO: assessing genome assembly and annotation completeness with single-copy orthologs.

              Genomics has revolutionized biological research, but quality assessment of the resulting assembled sequences is complicated and remains mostly limited to technical measures like N50.
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                Journal
                Plant Physiology
                Oxford University Press (OUP)
                0032-0889
                1532-2548
                March 24 2023
                March 24 2023
                Article
                10.1093/plphys/kiad183
                36960567
                9a471991-7393-45c8-9129-45ae8475bd3a
                © 2023
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