Simon Andrews

Simon Andrews
Simon Andrews
Simon Andrews
Head of Bioinformatics Facility
Simon Andrews

Simon Andrews did his first degree in Microbiology at the University of Warwick.  After a brief period working for Sandoz pharmaceuticals he went on  to do a PhD in protein engineering a the University of Newcastle with Harry Gilbert.  During his PhD his interests moved from bench work toward the emerging field of bioinformatics, and he decided to follow this direction in his future career.

After completing his PhD Simon worked with the BBSRC IT Services where he developed and then presented a series of bioinformatics training courses in protein structure analysis to the BBSRC institutes.  At one of these courses at Babraham he met John Coadwell who establised the Babraham Bioinformatics group and was then employed as the second member of the bioinformatics team.  Since joining Babraham Simon has seen the group grow from two people to nine as the field has become far more prominent in the biological research community.  He took over the running of the group in 2010.

Latest Publications

Rostovskaya M, Andrews S, Reik W, Rugg-Gunn PJ Epigenetics, Bioinformatics

In primates, the amnion emerges through cavitation of the epiblast during implantation, whereas in other species it does so later at gastrulation by the folding of the ectoderm. How the mechanisms of amniogenesis diversified during evolution remains unknown. Unexpectedly, single-cell analysis of primate embryos uncovered two transcriptionally and temporally distinct amniogenesis waves. To study this, we employed the naive-to-primed transition of human pluripotent stem cells (hPSCs) to model peri-implantation epiblast development. Partially primed hPSCs transiently gained the ability to differentiate into cavitating epithelium that transcriptionally and morphologically matched the early amnion, whereas fully primed hPSCs produced cells resembling the late amnion instead, thus recapitulating the two independent differentiation waves. The early wave follows a trophectoderm-like pathway and encompasses cavitation, whereas the late wave resembles an ectoderm-like route during gastrulation. The discovery of two independent waves explains how amniogenesis through cavitation could emerge during evolution via duplication of the pre-existing trophectoderm program.

+view abstract Cell stem cell, PMID: 35439430 05 May 2022

Hanna CW, Huang J, Belton C, Reinhardt S, Dahl A, Andrews S, Stewart AF, Kranz A, Kelsey G Epigenetics, Bioinformatics

Histone 3 lysine 4 trimethylation (H3K4me3) is an epigenetic mark found at gene promoters and CpG islands. H3K4me3 is essential for mammalian development, yet mechanisms underlying its genomic targeting are poorly understood. H3K4me3 methyltransferases SETD1B and MLL2 (KMT2B) are essential for oogenesis. We investigated changes in H3K4me3 in Setd1b conditional knockout (cKO) oocytes using ultra-low input ChIP-seq, with comparisons to DNA methylation and gene expression analyses. H3K4me3 was redistributed in Setd1b cKO oocytes showing losses at active gene promoters associated with downregulated gene expression. Remarkably, many regions also gained H3K4me3, in particular those that were DNA hypomethylated, transcriptionally inactive and CpG-rich, which are hallmarks of MLL2 targets. Consequently, loss of SETD1B disrupts the balance between MLL2 and de novo DNA methyltransferases in determining the epigenetic landscape during oogenesis. Our work reveals two distinct, complementary mechanisms of genomic targeting of H3K4me3 in oogenesis, with SETD1B linked to gene expression and MLL2 to CpG content.

+view abstract Nucleic acids research, PMID: 35137160 07 Feb 2022

Suriyalaksh M, Raimondi C, Mains A, Segonds-Pichon A, Mukhtar S, Murdoch S, Aldunate R, Krueger F, Guimerà R, Andrews S, Sales-Pardo M, Casanueva O Epigenetics, Bioinformatics

We design a "wisdom-of-the-crowds" GRN inference pipeline and couple it to complex network analysis to understand the organizational principles governing gene regulation in long-lived /Notch . The GRN has three layers (input, core, and output) and is topologically equivalent to bow-tie/hourglass structures prevalent among metabolic networks. To assess the functional importance of structural layers, we screened 80% of regulators and discovered 50 new aging genes, 86% with human orthologues. Genes essential for longevity-including ones involved in insulin-like signaling (ILS)-are at the core, indicating that GRN's structure is predictive of functionality. We used reporters and a novel functional network covering 5,497 genetic interactions to make mechanistic predictions. We used genetic epistasis to test some of these predictions, uncovering a novel transcriptional regulator, , that works alongside DAF-16/FOXO. We present a framework with predictive power that can accelerate discovery in and potentially humans.

+view abstract iScience, PMID: 35036864 21 Jan 2022

Group Members

Simon Andrews

Head of Bioinformatics Facility

Laura Biggins

Core Bioinformatician

Caroline Gaud

LIPID MAPS Web Developer

Sarah Inglesfield

Core Bioinformatician

Jo Montgomery

Biological Training Developer

Anne Segonds-Pichon

Biological Statistician