Cobalt-Catalyzed 1,1,3-Triborylation of Terminal Alkynes

We have developed a cobalt-catalyzed regioselective 1,1,3-triborylation reaction of terminal alkynes with pinacolborane (HBpin) with a catalyst generated in situ from readily available and bench-stable Co­(acac)2 and xantphos. A variety of terminal alkynes undergo this triborylation reaction, affording the corresponding 1,1,3-triborylalkanes in good yields with high selectivity. The synthetic utility of this catalytic protocol has been demonstrated by developing selective stepwise functionalization of 1,1,3-triborylalkane products. The results of mechanistic studies, such as conducting control experiments and deuterium-labeling reactions, monitoring the reaction process, and identifying reaction intermediates, suggest that this 1,1,3-triborylation reaction proceeds through 1,3-diborylation of alken-1-ylboronates formed by cobalt-catalyzed hydroboration of terminal alkynes

Candidate gene (<i>PHA-E</i>) and phytohemagglutinin content in snap bean (<i>Phaseolus vulgaris</i> L.): an association study

Snap bean (Phaseolus vulgaris L.) is low in fat and high in nutrients; however, it also contains toxigenic factors such as phytohemagglutinin (PHA), which is poisonous to humans. Here, we aimed to determine the distribution of PHA in natural populations of snap bean by analyzing a candidate gene (PHA-E) related to PHA content. Functional genome-wide single nucleotide polymorphisms (SNPs) were then scanned to identify SNPs related to PHA content. A total of 150 snap bean varieties were examined. PHA content and PHA-E expression levels were determined 10, 14, 18, 22, 26 and 30 days after anthesis. Then, association analyses were carried out to identify causal SNPs in PHA-E via genotyping and association tests. PHA-E expression was positively-correlated with PHA content. Among 59 detected SNPs, the ratio of synonymous to nonsynonymous changes was 1:8. P190 was identified as a novel SNP associated with PHA content. The allele carrying the GG genotype at P190 was detected in 130 varieties, of which 86 had an above-average PHA content, while the allele carrying the AA genotype at P190 was detected in 20 varieties, of which 17 (85%) had a low PHA content. Analyses of the PHA content and gene expression in fresh pods of 150 snap bean cultivars revealed population-level distribution and genetic variation, providing a unique measure for screening of low-level or nontoxic cultivars and aiding future breeding of new cultivars. Supplemental data for this article is available online at https://doi.org/10.1080/13102818.2021.1985613.</p

Additional file 1 of Possible melatonin-induced salt stress tolerance pathway in Phaseolus vulgaris L. using transcriptomic and metabolomic analyses

Supplementary Material 1: List of cultivars and growth habit in this stud

Distinctive types of postzygotic single-nucleotide mosaicisms in healthy individuals revealed by genome-wide profiling of multiple organs

<div><p>Postzygotic single-nucleotide mosaicisms (pSNMs) have been extensively studied in tumors and are known to play critical roles in tumorigenesis. However, the patterns and origin of pSNMs in normal organs of healthy humans remain largely unknown. Using whole-genome sequencing and ultra-deep amplicon re-sequencing, we identified and validated 164 pSNMs from 27 postmortem organ samples obtained from five healthy donors. The mutant allele fractions ranged from 1.0% to 29.7%. Inter- and intra-organ comparison revealed two distinctive types of pSNMs, with about half originating during early embryogenesis (embryonic pSNMs) and the remaining more likely to result from clonal expansion events that had occurred more recently (clonal expansion pSNMs). Compared to clonal expansion pSNMs, embryonic pSNMs had higher proportion of C>T mutations with elevated mutation rate at CpG sites. We observed differences in replication timing between these two types of pSNMs, with embryonic and clonal expansion pSNMs enriched in early- and late-replicating regions, respectively. An increased number of embryonic pSNMs were located in open chromatin states and topologically associating domains that transcribed embryonically. Our findings provide new insights into the origin and spatial distribution of postzygotic mosaicism during normal human development.</p></div

Identification and validation of pSNMs in 27 organ samples obtained from five individuals.

<p>(A) Genomic landscape of the validated pSNMs. Circos plots from outer to inner represent individuals BBL1100C, BBL11121, BBLC1013, BBLD1005, and BBLD1010, respectively. The Y axis denotes the average minor allele fraction across pSNM-carrying organs of each donor. (B) Correlation of the allele fractions estimated by whole-genome sequencing and targeted ultra-deep resequencing (PASM) of the validated sites. The shape, color, and size of the dots represent the donor and organ type carrying the pSNMs and the site-specific depth of whole-genome sequencing.</p

Distinct genomic characteristics between embryonic and clonal expansion pSNMs.

<p>(A-C) Mutation spectrums in NpG and non-NpG sites for embryonic pSNMs (A), clonal expansion pSNMs in BBLD1005’s liver (B), and clonal expansion pSNMs in BBL11121’s breast (C). Mutation rate was normalized by the total number of sites in the human genome. For embryonic pSNMs, CpG sites showed significantly higher rate of C>T mutations than non-CpG sites. (D) Varied DNA replication timing of the two pSNMs types. The grey line denotes the genomic average. Embryonic pSNMs were enriched in early-replicating regions, whereas clonal expansion pSNMs were enriched in late-replicating regions. (E-G) Proportion of pSNMs locating in open or closed chromatin regions in the HepG2 (E), HMEC (F), and K562 (G) cell-lines. Significantly higher proportions of embryonic pSNMs were observed in transcribed chromatin regions of all three cell types.</p

“Bioinformatics: Introduction and Methods,” a Bilingual Massive Open Online Course (MOOC) as a New Example for Global Bioinformatics Education

<p>“Bioinformatics: Introduction and Methods,” a Bilingual Massive Open Online Course (MOOC) as a New Example for Global Bioinformatics Education</p

Two types of pSNMs revealed by inter- and intra-organ profiles.

<p>(A) Minor allele fractions between different categories of pSNM. The organ-shared pSNMs demonstrated significantly higher allele fractions than the organ-unique pSNMs. (B) Number of pSNMs carried in different organ samples. Red and blue bars denote the organ-shared and organ-unique pSNMs, respectively. An excess of organ-unique pSNMs was observed in the breast sample of BBL11121 and the liver sample of BBLD1005. (C-D) Heatmap of minor allele fractions for pSNMs carried in multiple organ samples of BBLD1005 (C) and BBL11121 (D). Blood samples of two unrelated individuals (ACC1 and ACC4) served as negative controls. The color intensity of each tile represents allele fractions estimated by targeted ultra-depth resequencing. Gray tiles denote sites without sufficient read depth (< 30X). Red and blue bars denote the organ-shared and organ-unique pSNMs, respectively. The majority of organ-unique pSNMs were locally restricted to one or a few physically adjacent organ samples (<1 cm). (E-F) Relative intra-organ similarity of pSNM profiles in BBLD1005 (E) and BBL11121 (F). The originally sequenced samples (liver #9 and breast #9) shared the largest similarity to their physically closest samples.</p

Data_Sheet_1_RJAfinder: An automated tool for quantification of responding to joint attention behaviors in autism spectrum disorder using eye tracking data.zip

Deficits in responding to joint attention (RJA) are early symptoms of autism spectrum disorder (ASD). Currently, no automated tools exist for identifying and quantifying RJA behaviors. A few eye tracking studies have investigated RJA in ASD children but have produced conflicting results. In addition, little is known about the trajectory of RJA development through developmental age. Here, a new video was designed including 12 clips of an actor pointing to or looking at an object. Eye tracking technology was used to monitor RJA in three groups: 143 ASD children assessed with the Autism Diagnostic Interview-Revised (ADI-R) and the Autism Diagnostic Observation Schedule (ADOS) (4–7 years old), 113 age- and gender-matched typically developing children (TDC), and 43 typically developing adults (TDA) (19–32 years old). RJAfinder was developed in R and MATLAB to quantify RJA events from the eye tracking data. RJA events were compared among the three groups. Spearman correlation coefficients between total number of RJA events in ASD and the Social Responsiveness Scale (SRS) scores were calculated. A logistic regression model was built using the average valid sampling rate and the total number of RJA events as two predictive variables to classify ASD and TDC groups. ASD children displayed statistically significantly less RJA events than the TDC and TDA groups with medium-to-large-sized effects. ASD and TDC children both displayed more RJA events in response to pointing stimuli than to looking stimuli. Our logistic regression model predicted ASD tendency with 0.76 accuracy in the testing set. RJA ability improved more slowly between the ages of 4–7 years old in the ASD group than in the TDC group. In ASD children, RJA ability showed negative correlation with SRS total T-score as well as the scores of five subdomains. Our study provides an automated tool for quantifying RJA and insights for the study of RJA in ASD children, which may help improve ASD screening, subtyping, and behavior interventions.</p

Donor and sequencing information regarding the 27 post-mortem organ samples profiled in this study.

<p>Donor and sequencing information regarding the 27 post-mortem organ samples profiled in this study.</p