Biomedical subjects

Andrew Olson

Publications and source records attributed to Andrew Olson.

5 recordsLinked to original sources

PubMed2025

Decoding nitrogen uptake efficiency in maize and sorghum: insights from comparative gene regulatory networks.

Nitrogen (N) is an essential macronutrient for plant growth and yield, yet optimizing nitrogen use efficiency remains a challenge in agriculture. To better understand the regulatory basis of plant responses to N availability, we constructed a maize-specific nitrogen uptake efficiency gene regulatory network (mNUEGRN) comprising 1625 protein-DNA interactions (PDI) between 70 promoters and 301 transcription factors using enhanced yeast one-hybrid assays. We also projected a sorghum NUE GRN (spNUEGRN) based on maize orthologs and analyzed N-responsive subnetworks in both species using transcriptome profiling under N stress of early deprivation and recovery. Cross-species comparison with an existing Arabidopsis GRN revealed about 18% conserved interaction, corresponding to 11% of the mNUEGRN, particularly within the nitrate assimilation pathways. Notably, bZIP18 and bZIP30 emerged as central regulators in mNUEGRN, forming highly connected feed-forward loops (FFLs). From our time series data, we identified 19 236 and 23 864 differentially expressed genes in maize and sorghum, respectively. Gini correlation analysis uncovered 764 and 638 FFLs in mNUEGRN and spNUEGRN, respectively, of which 22 FFLs in maize and 35 in sorghum were identified in both leaf and root for each species. These FFLs may represent candidate regulatory motifs that contribute to modulating transcriptional responses under fluctuating N conditions, but their potential roles require further investigation. Together, our findings reveal evolutionarily conserved and species-specific regulatory strategies that mediate early N responsiveness, offering a foundation for engineering crops with improved NUE.

Sorghum↗

PubMed2004

Bridging expressed sequence alignments through targeted cDNA sequencing.

One of the major challenges in genome research is the identification of the complete set of genes in a genome. Alignments of expressed sequences (RNA and EST) with genomic sequences have been used to characterize genes. However, the number of alignments far exceeds the likely number of genes in a genome, suggesting that, for many genes, two or more alignments can be joined through overlapping sequences to yield accurate gene structures. High-throughput EST sequencing becomes less efficient in closing those alignment gaps due to its nonselective nature. We sought to bridge these alignments through a novel approach: targeted cDNA sequencing. Human expressed sequences from GenBank version 124 were aligned with the genomic sequence from NCBI build 24 using LEADS, Compugen's EST and RNA clustering and assembly software system. Nine hundred forty-eight pairs of alignments were selected based on EST clone information and/or their homology to the same known proteins. Reverse transcriptase PCR and sequencing yielded sequences for 363 of those pairs. These sequences helped characterize over 60 novel or otherwise incomplete genes in the recent UniGene build 153, which included over 1 million additional ESTs. These results indicate that this integrated and targeted strategy, combining computational prediction and experimental cDNA sequencing, can efficiently generate the overlapping sequences and enable the full characterization of genomes. Additional information about the contig pairs, the resultant overlapping sequences, tissue sources, and tissue profiles are available in a supplemental file.

Cloning, Molecular↗

PubMed2002

Computational analysis of alternative splicing using EST tissue information.

Expressed sequence tags (ESTs) from normal and tumor tissues have been deposited in public databases. These ESTs and all mRNA sequences were aligned with the human genome sequence using LEADS, Compugen's alternative splicing modeling platform. We developed a novel computational approach to analyze tissue information of aligned ESTs in order to identify cancer-specific alternative splicing and gene segments highly expressed in particular cancers. Several genes, including one encoding a possible pre-mRNA splicing factor, displayed cancer-specific alternative splicing. In addition, multiple candidate gene segments highly expressed in colon cancers were identified.

Alternative Splicing↗

PubMed2002

Patterns of phonological errors as a function of a phonological versus an articulatory locus of impairment.

We present the case of two aphasic patients: one with fluent speech, MM, and one with dysfluent speech, DB. Both patients make similar proportions of phonological errors in speech production and the errors have similar characteristics. A closer analysis, however, shows a number of differences. DB's phonological errors involve, for the most part, simplifications of syllabic structure; they affect consonants more than vowels; and, among vowels, they show effects of sonority/complexity. This error pattern may reflect articulatory difficulties. MM's errors, instead, show little effect of syllable structure, affect vowels at least as much as consonants and, and affect all different vowels to a similar extent. This pattern is consistent with a more central impairment involving the selection of the right phoneme among competing alternatives. We propose that, at this level, vowel selection may be more difficult than consonant selection because vowels belong to a smaller set of repeatedly activated units.

Aged↗

PubMed2002

Formal lexical paragraphias in a single case study: how "masterpiece" can become "misterpieman" and "curiosity" "suretoy".

Formal lexical errors are relatively rare in the production of aphasic patients. In this study, we report the case of DW, who makes a high proportion of these errors. A few other cases have previously been reported, but DW shows a number of distinguishing characteristics. First, formal lexical errors are made in spelling and not in spoken speech. Second, they are associated with morphological errors and not with semantic errors. Third, they often combine lexical units in ways which are semantically and morphologically illegal. Finally, the majority of morphological errors involve the insertion, rather than the deletion, of suffixes. This pattern can be explained by hypothesizing that DW's errors arise because of confusions among a cohort of lexical neighbors activated top-down from a phonological input and bottom-up from shared letters. One possible cause of the confusions is lack of proper inhibition among lexical competitors.

Aged↗