Nigel George Laing

Prof. Nigel George Laing

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Research Focus & Metrics

Academic Career Length

35Years (1992-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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19 April 2017 in Science Translational Medicine
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Journal Article
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BCBeryl B. Cummings
Beryl B. Cummings
JMJamie L. Marshall
Jamie L. Marshall
TTTaru Tukiainen
Taru Tukiainen
MLMonkol Lek
Monkol Lek
SDSandra Donkervoort
Sandra Donkervoort
DMDaniel G. MacArthur
Daniel G. MacArthur
Exome and whole-genome sequencing are becoming increasingly routine approaches in Mendelian disease diagnosis. Despite their success, the current diagnostic rate for genomic analyses across a variety of rare diseases is approximately 25 to 50%. We explore the utility of transcriptome sequencing [RNA sequencing (RNA-seq)] as a complementary diagnostic tool in a cohort of 50 patients with genetically undiagnosed rare muscle disorders. We describe an integrated approach to analyze patient muscle RNA-seq, leveraging an analysis framework focused on the detection of transcript-level changes that are unique to the patient compared to more than 180 control skeletal muscle samples. We demonstrate the power of RNA-seq to validate candidate splice-disrupting mutations and to identify splice-altering variants in both exonic and deep intronic regions, yielding an overall diagnosis rate of 35%. We also report the discovery of a highly recurrent de novo intronic mutation in COL6A1 that results in a dominantly acting splice-gain event, disrupting the critical glycine repeat motif of the triple helical domain. We identify this pathogenic variant in a total of 27 genetically unsolved patients in an external collagen VI–like dystrophy cohort, thus explaining approximately 25% of patients clinically suggestive of having collagen VI dystrophy in whom prior genetic analysis is negative. Overall, this study represents a large systematic application of transcriptome sequencing to rare disease diagnosis and highlights its utility for the detection and interpretation of variants missed by current standard diagnostic approaches.

1 October 1999 in Nature Genetics
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Journal Article
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KNKristen J. Nowak
Kristen J. Nowak
DWDuangrurdee Wattanasirichaigoon
Duangrurdee Wattanasirichaigoon
HGHans H. Goebel
Hans H. Goebel
MWMatthew Wilce
Matthew Wilce
KPKatarina Pelin
Katarina Pelin
NLNigel George Laing
Nigel George Laing

1 February 2014 in Neuromuscular Disorders
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Journal Article
Open access
Kathryn N. NorthKathryn N. North
Kathryn N. North
CWChing H. Wang
Ching H. Wang
NCNigel Clarke
Nigel Clarke
HJHeinz Jungbluth
Heinz Jungbluth
MVMariz Vainzof
Mariz Vainzof
CBCarsten G. Bönnemann
Carsten G. Bönnemann
Over the past decade there have been major advances in defining the genetic basis of the majority of congenital myopathy subtypes. However the relationship between each congenital myopathy, defined on histological grounds, and the genetic cause is complex. Many of the congenital myopathies are due to mutations in more than one gene, and mutations in the same gene can cause different muscle pathologies. The International Standard of Care Committee for Congenital Myopathies performed a literature review and consulted a group of experts in the field to develop a summary of (1) the key features common to all forms of congenital myopathy and (2) the specific features that help to discriminate between the different genetic subtypes. The consensus statement was refined by two rounds of on-line survey, and a three-day workshop. This consensus statement provides guidelines to the physician assessing the infant or child with hypotonia and weakness. We summarise the clinical features that are most suggestive of a congenital myopathy, the major differential diagnoses and the features on clinical examination, investigations, muscle pathology and muscle imaging that are suggestive of a specific genetic diagnosis to assist in prioritisation of genetic testing of known genes. As next generation sequencing becomes increasingly used as a diagnostic tool in clinical practise, these guidelines will assist in determining which sequence variations are likely to be pathogenic.

1 January 1995 in Nature Genetics
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Journal Article
Closed access
NLNigel George Laing
Nigel George Laing
SWSteve Wilton
Steve Wilton
PAPatrick A. Akkari
Patrick A. Akkari
SDShellie Dorosz
Shellie Dorosz
KBKaryn Boundy
Karyn Boundy
EHEric Haan
Eric Haan

25 May 2001 in Annals of Neurology
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Journal Article
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MRMonique M. Ryan
Monique M. Ryan
CSChristina Schnell
Christina Schnell
CSCorinne D. Strickland
Corinne D. Strickland
LSLloyd K. Shield
Lloyd K. Shield
GMGraeme Morgan
Graeme Morgan
Kathryn N. NorthKathryn N. North
Kathryn N. North

9 June 2009 in Human Mutation
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Journal Article
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NLNigel George Laing
Nigel George Laing
DDDanielle E. Dye
Danielle E. Dye
CWCarina Wallgren-Pettersson
Carina Wallgren-Pettersson
GRGabriele Richard
Gabriele Richard
NMNicole Monnier
Nicole Monnier
KNKristen J. Nowak
Kristen J. Nowak
The ACTA1 gene encodes skeletal muscle α‐actin, which is the predominant actin isoform in the sarcomeric thin filaments of adult skeletal muscle, and essential, along with myosin, for muscle contraction. ACTA1 disease‐causing mutations were first described in 1999, when a total of 15 mutations were known. In this article we describe 177 different disease‐causing ACTA1 mutations, including 85 that have not been described before. ACTA1 mutations result in five overlapping congenital myopathies: nemaline myopathy; intranuclear rod myopathy; actin filament aggregate myopathy; congenital fiber type disproportion; and myopathy with core‐like areas. Mixtures of these histopathological phenotypes may be seen in a single biopsy from one patient. Irrespective of the histopathology, the disease is frequently clinically severe, with many patients dying within the first year of life. Most mutations are dominant and most patients have de novo mutations not present in the peripheral blood DNA of either parent. Only 10% of mutations are recessive and they are genetic or functional null mutations. To aid molecular diagnosis and establishing genotype–phenotype correlations, we have developed a locus‐specific database for ACTA1 variations (http://waimr.uwa.edu.au). Hum Mutat 30:1–11, 2009.