Biology subjects

Iniguez, C.

Publications and source records attributed to Iniguez, C..

4 recordsLinked to original sources

bioRxiv2025

Diversity in Rubisco Kinetics and CO2-Concentrating Mechanisms Among Cyanobacterial Lineages

Cyanobacteria are the most ancient oxygenic photosynthetic organisms on Earth and play a pivotal role in the global carbon cycle. Despite their ecological and evolutionary significance, the mechanisms of carbon acquisition and fixation in this phylum remain largely unexplored beyond a few model species. Here, we examined representative taxa spanning the full phylogenetic breadth of Cyanobacteria, assessing in vivo carbon-acquisition pathways, the role and efectiveness of CO2-concentrating mechanisms (CCMs), as well as conducting in vitro biochemical characterizations of the kinetic traits and carbon isotope fractionation of Rubisco. We found significant lineage-specific diferences in Rubisco kinetics and CCM performance, but a common signature of high Rubisco catalytic turnover coupled with low CO2 afinity--consistent with the co-evolution of this enzyme together with powerful CCMs. Furthermore, we identified a strong positive correlation between Rubisco carbon isotope fractionation and its CO2/O2 specificity factor. Together, these results provide fresh insight into Rubisco catalysis and shed light on its co-evolution with CCMs, underscoring their role in shaping Earths carbon dynamics.

plant biology↗

bioRxiv2025

Singletrack: An Algorithm for Improving Memory Consumption and Performance of Gap-Affine Sequence Alignment

MotivationAdvances in DNA sequencing have outpaced advances in computation, making sequence alignment a major bottleneck in genome data analyses. Classical dynamic programming (DP) algorithms are particularly memory-intensive, especially when computing gap-affine and dual gap-affine alignments. Existing strategies to reduce memory consumption often sacrifice either speed or alignment accuracy. ResultsWe present Singletrack, an efficient algorithm for backtrace gap-affine and dual gap-affine alignments that requires only storing a single DP matrix. Compared to classical DP algorithms, Singletrack removes the need to store additional matrices (i.e., 2 for gap-affine and 4 for dual gap-affine), significantly reducing memory consumption and, in turn, reducing pressure on the memory hierarchy and improving overall performance. Most importantly, Singletrack is a general backtrace method compatible with state-of-the-art DP-based algorithms and heuristics, such as the Suzuki-Kasahara (SK) and the Wavefront Alignment (WFA) algorithms. Our results demonstrate that Singletrack accelerates the SK implementation of KSW2, used within Minimap2, by up to 1.4x. Similarly, Singletrack enhances the performance of the WFA implementation in WFA2-lib by 1.2-2.1x while reducing memory usage by 3x for gap-affine and 5x for dual gap-affine. Compared to the efficient linear-memory BiWFA algorithm, the Singletrack-accelerated version of WFA trades a practical increase in memory usage for up to 5.2x higher performance. AvailabilityAll the implementations of the Singletrack algorithm presented in this work are available at https://github.com/LorienLV/singletrack.

bioinformatics↗

bioRxiv2024

QuickEd: High-performance exact sequence alignment based on bound-and-align

MotivationPairwise sequence alignment is a core component of multiple sequencing-data analysis tools. Recent advancements in sequencing technologies have enabled the generation of longer sequences at a much lower price. Thus, long-read sequencing technologies have become increasingly popular in sequencing-based studies. However, classical sequence analysis algorithms face significant scalability challenges when aligning long sequences. As a result, several heuristic methods have been developed to improve performance at the expense of accuracy, as they often fail to produce the optimal alignment. ResultsThis paper introduces QuickEd, a sequence alignment algorithm based on a bound-and-align strategy. First, QuickEd effectively bounds the maximum alignment-score using efficient heuristic strategies. Then, QuickEd utilizes this bound to reduce the computations required to produce the optimal alignment. Using QuickEds bound-and-align strategy, we reduce O(n2) complexity of traditional dynamic programming algorithms to O(n[s]), where n is the sequence length and[s] is an estimated upper bound of the alignment-score between the sequences. As a result, QuickEd is consistently faster than other state-of-the-art implementations, such as Edlib and BiWFA, achieving performance speedups of 1.6-7.3x and 2.1 - 2.5x, respectively, aligning long and noisy datasets. In addition, QuickEd maintains a stable memory footprint below 50 MB while aligning sequences up to 1 Mbp. AvailabilityQuickEd code and documentation are publicly available at https://github.com/maxdoblas/QuickEd. Contactmax.doblas@bsc.es

bioinformatics↗

bioRxiv2019

Placental DNA methylation signatures of maternal smoking during pregnancy and potential impacts on fetal growth

Maternal smoking during pregnancy (MSDP) contributes to poor birth outcomes, in part through disrupted placental functions, which may be reflected in the placental epigenome. We meta-analyzed the associations between MSDP and placental DNA methylation (DNAm) and between DNAm and birth outcomes within the Pregnancy And Childhood Epigenetics (PACE) consortium (7 studies, N=1700, 344 with any MSDP). We identified 1224 CpGs that were associated with MSDP, of which 341 associated with birth outcomes and 141 associated with gene expression. Only 6 of these CpGs were consistent with the findings from a prior meta-analysis of cord blood DNAm, demonstrating substantial tissue-specific responses to MSDP. The placental MSDP associated CpGs were enriched for growth-factor signaling, hormone activity, inflammation, and vascularization, which play important roles in placental function. We demonstrate links between placental DNAm, MSDP and poor birth outcomes, which may better inform the mechanisms through which MSDP impacts placental function and fetal growth.

genomics↗